{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1e4c6980",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm.notebook import tqdm\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "from itertools import product\n",
    "from itertools import accumulate\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "from itertools import accumulate\n",
    "def BARSLAST(series_1):\n",
    "    return pd.Series(np.array(list(accumulate(~series_1, lambda x, y: (x + y) * y))), index=series_1.index)\n",
    "    \n",
    "def cal年化收益率(dd):\n",
    "    return (250**1)*dd.mean()\n",
    "\n",
    "def cal夏普比率(dd):\n",
    "    return (250**0.5)*dd.mean()/dd.std()\n",
    " \n",
    "def cal收益平均回撤(dd):\n",
    "    return (250*dd.mean())/((dd.cumsum().cummax() - dd.cumsum()).sum()/len(dd))\n",
    "\n",
    "def cal最大回撤(dd):\n",
    "    return (dd.cumsum().cummax() - dd.cumsum()).max()\n",
    "\n",
    "def cal收益最大回撤(dd):\n",
    "    return (250*dd.mean())/(dd.cumsum().cummax() - dd.cumsum()).max()\n",
    "\n",
    "def cal周度胜率(dd):\n",
    "    return (dd.resample('W').sum() > 0).sum()/(dd.resample('W').sum() != 0).sum()\n",
    "\n",
    "def cal周度盈亏比(dd):\n",
    "    pp = dd.resample('W').sum()\n",
    "    平均盈利 = (pp*(pp>0)).sum()/(pp>0).sum()\n",
    "    平均亏损 = (pp*(pp<0)).sum()/(pp<0).sum()\n",
    "    return -平均盈利/平均亏损\n",
    "\n",
    "def cal最大下潜期(dd):\n",
    "    return BARSLAST(dd.cumsum() / dd.cumsum().cummax() == 1).max()\n",
    "    \n",
    "def cal最大下潜期结束时间(dd):\n",
    "    return str(dd.index[BARSLAST(dd.cumsum() / dd.cumsum().cummax() == 1).argmax()]).split()[0]\n",
    "\n",
    "def cal当前回撤(dd):\n",
    "    return (dd.cumsum().cummax() - dd.cumsum())[-1]\n",
    "\n",
    "def cal当前下潜期(dd):\n",
    "    return BARSLAST(dd.cumsum() / dd.cumsum().cummax() == 1)[-1]\n",
    "\n",
    "def calcal(dd):\n",
    "    return cal夏普比率(dd)*cal收益平均回撤(dd)*cal收益最大回撤(dd)*cal周度胜率(dd)*cal周度盈亏比(dd)\n",
    "\n",
    "def get_回撤s(dd):\n",
    "    下潜期 = BARSLAST(dd.cumsum() / dd.cumsum().cummax() == 1)\n",
    "    下潜期记录 = []\n",
    "    s = None\n",
    "    for i in range(1,len(下潜期)):\n",
    "        if 下潜期[i] == 1 and 下潜期[i-1] == 0:\n",
    "            s = i - 1\n",
    "        if s:\n",
    "            if 下潜期[i] == 0:\n",
    "                e = i\n",
    "                下潜期记录.append([s,e])\n",
    "                s = None\n",
    "\n",
    "    回撤s = [(dd[下潜期记录[i][0]:下潜期记录[i][1]].cumsum().cummax() - dd[下潜期记录[i][0]:下潜期记录[i][1]].cumsum()).max() \n",
    "     for i in range(len(下潜期记录))]\n",
    "    return sorted(回撤s,reverse=True)\n",
    "\n",
    "def get_下潜期s(dd):\n",
    "    下潜期 = BARSLAST(dd.cumsum() / dd.cumsum().cummax() == 1)\n",
    "    下潜期记录 = []\n",
    "    s = None\n",
    "    for i in range(1,len(下潜期)):\n",
    "        if 下潜期[i] == 1 and 下潜期[i-1] == 0:\n",
    "            s = i - 1\n",
    "        if s:\n",
    "            if 下潜期[i] == 0:\n",
    "                e = i\n",
    "                下潜期记录.append([s,e])\n",
    "                s = None\n",
    "    下潜期记录 = np.array(下潜期记录)\n",
    "    return sorted(下潜期记录[:,1] - 下潜期记录[:,0],reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5abd9cf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "14e6ff32",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3427.48"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "3451.42+3408.41-3432.35"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "0b7104d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['股指月度']][the_date:].cumsum().plot(figsize=(14,6),grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a74da437",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d86a2fef",
   "metadata": {},
   "outputs": [],
   "source": [
    "(1/df[the_date:].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fb03278d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "展期      0.063845\n",
       "动量      0.054033\n",
       "反转      0.085093\n",
       "国债      0.236686\n",
       "股指日度    0.023254\n",
       "股指月度    0.059614\n",
       "正套      0.182450\n",
       "反套      0.295025\n",
       "dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "the_date = '2022-01-01'\n",
    "df = pd.read_csv('dddd.csv',index_col=0,parse_dates=True)\n",
    "w = (1/df[the_date:].std())/(1/df[the_date:].std()).sum()\n",
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "665d1efb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "展期      0.064342\n",
       "动量      0.058451\n",
       "反转      0.083486\n",
       "国债      0.229600\n",
       "股指日度    0.024954\n",
       "股指月度    0.067843\n",
       "正套      0.180844\n",
       "反套      0.290480\n",
       "dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "the_date = '2020-01-01'\n",
    "df = pd.read_csv('dddd.csv',index_col=0,parse_dates=True)\n",
    "w = (1/df[the_date:].std())/(1/df[the_date:].std()).sum()\n",
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "7cd62531",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>展期</th>\n",
       "      <th>动量</th>\n",
       "      <th>反转</th>\n",
       "      <th>国债</th>\n",
       "      <th>股指日度</th>\n",
       "      <th>股指月度</th>\n",
       "      <th>正套</th>\n",
       "      <th>反套</th>\n",
       "      <th>组合</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>展期</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.118695</td>\n",
       "      <td>0.036522</td>\n",
       "      <td>0.064545</td>\n",
       "      <td>0.042061</td>\n",
       "      <td>-0.006484</td>\n",
       "      <td>0.413752</td>\n",
       "      <td>0.146598</td>\n",
       "      <td>0.452653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>动量</th>\n",
       "      <td>0.118695</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.103342</td>\n",
       "      <td>0.088104</td>\n",
       "      <td>0.121389</td>\n",
       "      <td>-0.106659</td>\n",
       "      <td>0.242957</td>\n",
       "      <td>0.051506</td>\n",
       "      <td>0.391745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反转</th>\n",
       "      <td>0.036522</td>\n",
       "      <td>-0.103342</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.032138</td>\n",
       "      <td>0.026324</td>\n",
       "      <td>-0.036682</td>\n",
       "      <td>-0.150479</td>\n",
       "      <td>0.352993</td>\n",
       "      <td>0.297109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国债</th>\n",
       "      <td>0.064545</td>\n",
       "      <td>0.088104</td>\n",
       "      <td>-0.032138</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.015714</td>\n",
       "      <td>0.192603</td>\n",
       "      <td>0.019688</td>\n",
       "      <td>0.085056</td>\n",
       "      <td>0.366840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股指日度</th>\n",
       "      <td>0.042061</td>\n",
       "      <td>0.121389</td>\n",
       "      <td>0.026324</td>\n",
       "      <td>0.015714</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.066661</td>\n",
       "      <td>0.130297</td>\n",
       "      <td>0.161622</td>\n",
       "      <td>0.455697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股指月度</th>\n",
       "      <td>-0.006484</td>\n",
       "      <td>-0.106659</td>\n",
       "      <td>-0.036682</td>\n",
       "      <td>0.192603</td>\n",
       "      <td>0.066661</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.013418</td>\n",
       "      <td>0.042837</td>\n",
       "      <td>0.269087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>正套</th>\n",
       "      <td>0.413752</td>\n",
       "      <td>0.242957</td>\n",
       "      <td>-0.150479</td>\n",
       "      <td>0.019688</td>\n",
       "      <td>0.130297</td>\n",
       "      <td>-0.013418</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.288039</td>\n",
       "      <td>0.499589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反套</th>\n",
       "      <td>0.146598</td>\n",
       "      <td>0.051506</td>\n",
       "      <td>0.352993</td>\n",
       "      <td>0.085056</td>\n",
       "      <td>0.161622</td>\n",
       "      <td>0.042837</td>\n",
       "      <td>0.288039</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.578753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>组合</th>\n",
       "      <td>0.452653</td>\n",
       "      <td>0.391745</td>\n",
       "      <td>0.297109</td>\n",
       "      <td>0.366840</td>\n",
       "      <td>0.455697</td>\n",
       "      <td>0.269087</td>\n",
       "      <td>0.499589</td>\n",
       "      <td>0.578753</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            展期        动量        反转        国债      股指日度      股指月度        正套  \\\n",
       "展期    1.000000  0.118695  0.036522  0.064545  0.042061 -0.006484  0.413752   \n",
       "动量    0.118695  1.000000 -0.103342  0.088104  0.121389 -0.106659  0.242957   \n",
       "反转    0.036522 -0.103342  1.000000 -0.032138  0.026324 -0.036682 -0.150479   \n",
       "国债    0.064545  0.088104 -0.032138  1.000000  0.015714  0.192603  0.019688   \n",
       "股指日度  0.042061  0.121389  0.026324  0.015714  1.000000  0.066661  0.130297   \n",
       "股指月度 -0.006484 -0.106659 -0.036682  0.192603  0.066661  1.000000 -0.013418   \n",
       "正套    0.413752  0.242957 -0.150479  0.019688  0.130297 -0.013418  1.000000   \n",
       "反套    0.146598  0.051506  0.352993  0.085056  0.161622  0.042837  0.288039   \n",
       "组合    0.452653  0.391745  0.297109  0.366840  0.455697  0.269087  0.499589   \n",
       "\n",
       "            反套        组合  \n",
       "展期    0.146598  0.452653  \n",
       "动量    0.051506  0.391745  \n",
       "反转    0.352993  0.297109  \n",
       "国债    0.085056  0.366840  \n",
       "股指日度  0.161622  0.455697  \n",
       "股指月度  0.042837  0.269087  \n",
       "正套    0.288039  0.499589  \n",
       "反套    1.000000  0.578753  \n",
       "组合    0.578753  1.000000  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('W').sum().corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b01a239",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1e5118b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "展期      0.063845\n",
       "动量      0.054033\n",
       "反转      0.085093\n",
       "国债      0.236686\n",
       "股指日度    0.023254\n",
       "股指月度    0.059614\n",
       "正套      0.182450\n",
       "反套      0.295025\n",
       "dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8cefc6ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>展期</th>\n",
       "      <th>动量</th>\n",
       "      <th>反转</th>\n",
       "      <th>国债</th>\n",
       "      <th>股指日度</th>\n",
       "      <th>股指月度</th>\n",
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       "      <th>反套</th>\n",
       "      <th>组合</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>0.002350</td>\n",
       "      <td>0.012269</td>\n",
       "      <td>0.010163</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.010095</td>\n",
       "      <td>0.001409</td>\n",
       "      <td>-0.001315</td>\n",
       "      <td>0.000894</td>\n",
       "      <td>0.002040</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>-0.000575</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.000182</td>\n",
       "      <td>-0.000907</td>\n",
       "      <td>0.010248</td>\n",
       "      <td>-0.009234</td>\n",
       "      <td>0.000193</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>0.000022</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>-0.004383</td>\n",
       "      <td>0.005213</td>\n",
       "      <td>0.004223</td>\n",
       "      <td>-0.001353</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>0.008079</td>\n",
       "      <td>0.003273</td>\n",
       "      <td>-0.000932</td>\n",
       "      <td>0.000825</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.006896</td>\n",
       "      <td>0.006550</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>-0.004476</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>0.000351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.001898</td>\n",
       "      <td>-0.004110</td>\n",
       "      <td>-0.002855</td>\n",
       "      <td>0.001007</td>\n",
       "      <td>0.008952</td>\n",
       "      <td>-0.001867</td>\n",
       "      <td>0.001506</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.000378</td>\n",
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       "    <tr>\n",
       "      <th>2024-07-17</th>\n",
       "      <td>0.003319</td>\n",
       "      <td>-0.000688</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>0.004134</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.000534</td>\n",
       "      <td>0.001055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-18</th>\n",
       "      <td>0.000896</td>\n",
       "      <td>-0.003272</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>-0.000662</td>\n",
       "      <td>-0.005736</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>-0.000056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-19</th>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.004630</td>\n",
       "      <td>-0.000326</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.006807</td>\n",
       "      <td>0.002961</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>0.000093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>618 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  展期        动量        反转        国债      股指日度      股指月度  \\\n",
       "2022-01-04  0.002350  0.012269  0.010163  0.000083  0.010095  0.001409   \n",
       "2022-01-05 -0.000575 -0.001892 -0.000182 -0.000907  0.010248 -0.009234   \n",
       "2022-01-06 -0.004383  0.005213  0.004223 -0.001353 -0.000859  0.008079   \n",
       "2022-01-07  0.006896  0.006550  0.000121  0.000083  0.003895 -0.004476   \n",
       "2022-01-10  0.001898 -0.004110 -0.002855  0.001007  0.008952 -0.001867   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2024-07-17  0.003319 -0.000688 -0.000396  0.000316  0.004925  0.004134   \n",
       "2024-07-18  0.000896 -0.003272  0.001935 -0.000662 -0.005736  0.000263   \n",
       "2024-07-19 -0.002407 -0.004630 -0.000326  0.000929  0.006807  0.002961   \n",
       "2024-07-22       NaN       NaN       NaN       NaN  0.021351       NaN   \n",
       "2024-07-23       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "                  正套        反套        组合  \n",
       "2022-01-04 -0.001315  0.000894  0.002040  \n",
       "2022-01-05  0.000193  0.002264  0.000022  \n",
       "2022-01-06  0.003273 -0.000932  0.000825  \n",
       "2022-01-07  0.000685 -0.001430  0.000351  \n",
       "2022-01-10  0.001506  0.000379  0.000378  \n",
       "...              ...       ...       ...  \n",
       "2024-07-17  0.001755  0.000534  0.001055  \n",
       "2024-07-18  0.000095  0.000530 -0.000056  \n",
       "2024-07-19  0.000121 -0.000175  0.000093  \n",
       "2024-07-22       NaN       NaN  0.000496  \n",
       "2024-07-23       NaN       NaN  0.000000  \n",
       "\n",
       "[618 rows x 9 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ed9a62c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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9NaxDK/n52MwuDy0MwQ4AAAAAAHVU5qzWb9/bJklas79mps6siV01unNrM8tCC0awAwAAAADA9ypdbh0qrFBogI9ah/hLktweQ5sOFmptRoG+2XHsuDZT+8af7zIBL4IdAAAAAECL5DGkdzYcVtqREmXmlelAfrmyHRUyjJr348P81T46WG6PodX7873trBYpLixAh4sqdMvwdgr05VdrmIfvPgAAAABAi/TlIYu+WLP9uONBvjaVVbmV7ahUtqNSkuTrY9VFXVprcLtIXdAxWsmRgVq6K0cXdo4+32UDtRDsAAAAAACavUqXW1uyihQd4qfkyEDtOVaqbw5bJUnXDUlW36QItY0KVNtWQYoM8lVOiVMfb87Wnz/fIUn69ZgU/XJMx1rXnNA99rzfB/C/CHYAAAAAAM3e377cpVdWZEiS7DaLrBaLXIZFwzpE6vHLeshiqb09eUyov24f2V7B/j7adbREt49sb0bZwGkR7AAAAAAAmr1thxySJJvVIpfbkGSoXYihOT/rdVyo81PTBiWfpwqBM0OwAwAAAABo9g4XVUiS3r5ziGLDApTrKNf+TSvUKsjX5MqAs2M1uwAAAAAAAM6lardHR4trFkFOjAhUQniAuseHynbyiTpAk0GwAwAAAABo1nJKnHJ7DNltFkUH+5ldDtCg6hXspKWlaeDAgYqIiNDMmTNlGEad2u3du1eRkZHHHV+2bJm6du2qqKgozZkzpz6lAAAAAABQJ9nfP4YVG+Yvq5VpOmhe6hzsOJ1OTZ48Wf3791dqaqrS09M1b96807bLyMjQpEmTVFhYWOt4bm6upkyZomnTpmn16tVasGCBli5dWu8bAAAAAADgVH5YXyc+LMDkSoCGV+dgZ9GiRXI4HJozZ446dOigJ554Qq+88spp202aNEm33XbbcccXLFiguLg4Pfzww+rYsaMeeeSROl0PAAAAAID6+CHYSYgg2EHzU+ddsbZs2aIhQ4YoMDBQktSrVy+lp6eftt2nn34qq9Wq3/zmN8ddb8yYMd5t5QYNGqRZs2ad8lpOp1NOp9P7uri4WJLkcrnkcrnqeium+6HWplRzc0Hfm48xMB9jYD7GwFz0v7no/8aBcTAfY3B+HSookyTFhvgd1/eMgTno/9Ora99YjDoulHP//fersrJSzz//vPdYdHS0du/erYiIiFO2zczMVLt27WqtyXPllVdqyJAhmjlzpiSprKxM8fHxcjgcJ73Oo48+qscee+y442+++aY3cAIAAAAA4AdVbunpbTYdrbDomvZuDYup21qxgNnKy8s1ffp0ORwOhYaGnvS8Os/Y8fHxkZ9f7dXD/f39VV5eftpgpy7X++FapzJr1izdd9993tfFxcVKSkrS+PHjT3mTjY3L5dLixYs1btw42e12s8tpUeh78zEG5mMMzMcYmIv+Nxf93zgwDuZjDM6fxz/bqaMVBxURaNc9V41SdEjN76GMgbno/9P74Sml06lzsBMZGam0tLRax0pKSuTr61u/yn5yvdzc3Hpdy8/P77hwSZLsdnuT/EZoqnU3B/S9+RgD8zEG5mMMzEX/m4v+bxwYB/MxBudWeVW13t14WJI05+o+io8MPu4cxsBc9P/J1bVf6rx48sCBA7VmzRrv68zMTDmdzhNuY34m19u8ebMSEhLO6FoAAAAAgOYvt8SpJz7foYy8sjqdvzj9mMqr3GrTKlAXdo4+x9UB5qhzsDNy5Eg5HA7Nnz9fkjR79myNHTtWNptNxcXF9V7waMqUKVqxYoWWLl2q6upqPfXUU5owYUL9qgcAAAAAtBh//WKn5i7fr1v/s14VVe7Tnv/R5mxJ0mV9Erwb9wDNTZ2DHR8fH82dO1d33XWXYmJi9O6772r27NmSanbI+uyzz+r1wVFRUXr66ac1YcIExcXFKS0tTQ899FD9qgcAAAAAtAiFZVX6ZEtNULM/t0xPfL7jlOd7PIbWZxRIkiZ0jznn9QFmqfMaO5I0depU7dmzR6mpqRo2bJiio2umsmVmZp6yXdu2bXWizbdmzJih8ePHa8eOHRo1alSTWgAZAAAAAHD+vLfxkJzVHrUO8VNOiVOvrzmgMV1aa3SX1ic8/1BhhUqc1fL1sapTTMh5rhY4f+oV7EhSQkJCg66Fk5KSopSUlAa7HgAAAACg+VmyM0eSNOPCDjpYUKFXV2Zo5rtb9MW9IxUVfPwmO9uzHZKkzjEhstvq/LAK0OTw3Q0AAAAAaNQqqtxKzSyUJI3oFK3fXNxZnWKClVdapQff23bCJ0TSj9RsFd0tjidD0LwR7AAAAAAAGrX1mQWqcnsUH+av9lFB8rfb9Mw1feVrs+rrHcf03/VZx7XZnv19sBNPsIPmjWAHAAAAANCoLd+dK0kanhLl3d2qW3yoHpjQSZL0x0/Ste2QwztzJzOvTGv350uSuhPsoJkj2AEAAAAANEqVLrf25pTqo+93w7qoa+3drW67oL2Gtm+lCpdbk/+5Qje+tl7lVdW68/UNKqtyq19yuPomR5hROnDeEOwAAAAAABqdb3fl6KKnl2nsnGXKLXEqMshXY/5nByyr1aKnr+6tTjHBkmpm9kx/aa12HStRVLCfXryuv2xWixnlA+cNwQ4AAAAAoNHIL3Xq3v9u0k2vrdfhogrv8al9EuTrc/yvsPHhAfry3pGa0jtekrQ5q0g+VotevK6fYkL9z1vdgFnqvd05AAAAAADnQm6JU1e8uFJZBRWyWqSbh7dT76RwfZ1+THeNan/SdhaLRTcOa6OPv39k6+FLu2lg28jzVTZgKoIdAAAAAIDpPB5DMxZsUFZBhZIiA/TctH7qkxQuSd7ZOKfSLzlCD4zvJLvNqhuGtjnH1QKNB8EOAAAAAMB0n6cd0frMQgX52jTv5kHqEB1cr/YWi0W/HNPxHFUHNF6ssQMAAAAAMJWz2q2nv9otSbp9ZPt6hzpAS0awAwAAAAAw1bPf7FFGXpmigv1024iTr6UD4HgEOwAAAAAA0xx1VOrfy/ZLkv40tbuC/VgxBKgPgh0AAAAAgGk+3HxY1R5DA9pE6OIecWaXAzQ5RKEAAAAA0IR9siVbb6dmqaCsSkXlLknSv67rr56JYSc83+Mx9PsP0xTi76PrBrfRzqPFcnsMuQ1DsaH+GnAetwk3DEPvbzwkSbqyf+J5+1ygOSHYAQAAAIAmqNrtUWZ+mR54Z4uc1Z5a7724bK9euLb/CdttyirUwnUHJUlzl+8/7v1PfnnBSUOhhuSocGnmO1u0+1ipfH2smtiT2TrAmSDYAQAAAIBG6GB+ue59a5M6x4aqf5sIJUcGqn+bCNmsFmUVlOvmeeu1N6dUktS/TYR+OTpF5VVu3f3mRi1OP6a8Uqeigv2Ou+63u3Jrve4SG6IQfx9l5JUpr7RKGw4U1CvYcVS49Ngn21VU7tJ94zqpR8Lp26YddmjGgo06WFAuX5tVT1zeU2EB9jp/JoAfEewAAAAAQCP0zDe7tfFgkTYeLPLOsIkItGtkp2h9tydPBWVVkiQ/H6v+NLWHusaFSpLmLg/TlkMO/XfdQf1yTMfjrrtsd02wc1X/RF3eN0HDOrSSxWLRU1/u0j+X7tWuY6V1rnF7dk1AcyC/XJK0Yk+e3vvFsBMGQ0ccFfrDR9s1uktrPfrxdjmrPUqMCNAL1/ZTr8TwevUNgB+xeDIAAAAANDJHHBX6eHO2JCnAbtOANhEKC7CrsNyljzZnq6CsSj0SQvXpry7Qd78d7Q11JOnm4e0kSf9etl8FZVXKLXGqsKxKhmFof26pth5ySJJ+M6GzhqdEyWKxSJI6xYZIknYdLa5TjW+nZumKF1bpQH65Qvx9FB3ipyq3R/e9vVnlVdXHnf+Hj7brq/RjmvX+NjmrPerfJkKf/WoEoQ5wlpixAwAAAADngWEYkuQNUk5l3spMVXsMDWoXqbfvHCqpZk2d1AOFWrY7V61D/HTt4Dby9Tn+3+qn9I7X3OX7lX6kWP0eX+w9HurvI6u15rMvSIlS61D/Wu06x9QEO7uPlcowjJPWWely6w8fbddbqVmSpNGdo/X3a/rIY0jj/75ce3JKNfbpZRrcvpWq3B5Vuz3ysVr1VfqxWte5fUQ7hQXy+BVwtgh2AAAAAOAcW5x+TH/6LF0BdpvmXN1HHaMDvO+9siJDr3y3X78YnaLOMSGq9nj05tqaR6/uHNnee56Pzaoh7VtpSPtWp/wsq9WiP1/eQ9e+vFblVW7v8eLKmlk0rUP8NOfq3se1axcVJLvNolJntQ4XVSgxIvC4cw7ml+sXCzZoe3axLBbp/nGdNOPCFG9g9O/r++u6l9cq21GpDzYdPmWdIztFn/J9AHVDsAMAAAAA59CWrCLd8Xqqvp+wo6nPr9RvL+6kVkbNLJ4Xv92rvNIqPfxhWq12HaKDNLpz6zP6zL7JEfrvHUP04rf7dHnfBI3oGK2DBeXKKihX94TQ42brSJKvj1Xto4K161iJdh4pOS7Y+Tr9mO57e7OKK6sVGeSrZ3/eVxd0jKp1Tv82EXp/xjB9tf2YAnyt8rVZZbNa9PBH22udd3nfBAX68uso0BD4SQIAAACAc8QwDD3x+Q4ZhjSobaTsPhat3Juvxz/bqR4RVsX0KFJeac0iyIkRAfK1WWWxSH4+Nj14SRfvTJgz0SsxXC9e9+OW551jQ9T5+3V0TqZHQph2HSvRlkNFGtstRlLNI2BzFu/WC9/ukyT1Sw7X89f2U1xYwAmv0TUutNaaP5Jkt1k164NtevyyHuqZEKaU1sFnfF8AaiPYAQAAAIAz9MGmQ3ph6T5Veww99bNe6t8mstb7i9KOam1GgXx9rPr7z/soPsxf/1mVqT9/vkNphVZd92qqpJo1b964bbAZt1BL3+RwvbfxkDYdLJIk5ZU69euFm7RqX74k6aZhbfW7iV1PuLbPqfx8ULKm9Ilnlg5wDvBTBQAAAAB1lJFXptX78nWosFwH8sv12bYj3vd+8+5WLbpnpHx9rHJ7DG077NBjn9Q8gnTXyPZKCK+Z4XLT8HbqmxSq219drZzKmrYjO0Ud91lm6JccIUnanFWkdRkF+tXCjTpW7FSgr02zr+ylKb3jz/jahDrAucFPFgAAAACcxutrDujzrUe0LrNAbo9R672xXWP07a4c7cst06Rnv5PbMJRVUC6Xu+a8dlFBmjE6pVabbnGheqCXW5uMttqU5dBlfRLO272cSqeYYAX62lTqrNbV/14tSUppHax/XddPKa1P/RgXAHMQ7AAAAABo8Y46KhUT6nfCLb4/2ny41sLGg9tFqnNsiBIjAtQlNlQjOkbpy+3H9OuFm7Qnp9R7np+PVRf3iNWDl3SRv9123HX9bNIfJ3aT3d54tvz2sVnVNzlcK/fWPHo1uXe8Zl/RU0F+/OoINFb8dAIAAABoMYzvt6b6aYDz4rf79Ncvdmps19Z6blo/Bfj+GMJszirS7z+oCXXGdYvRr8d0VM/EsOOue3GPWK353UVasTdPkYG+ahcdpLhQ/7Na/Ngsv5/YTR9sOqRRnVpreEqrE4ZdABoPgh0AAAAAzd4Pu1PNX31AQX4+mnFhB/nbbTriqPDu9vT1jhz9+fN0/WlqT7ncHr22MkPPfL1H5VVuDWkfqRev7Scf28kXDY4M8j2rNWgai27xoeoW383sMgDUEcEOAAAAgGbv7dQsvfRdhiTJWV2lP322o9b7PlaLqj2G3ttwWKM6tdaTX+z0PlZ1QUqU/n19/1OGOgBgFoIdAAAAAM1aTkmlHv+0Jsi5c2R7hQbYtWRnjiIC7YoJ9Ve7qCBNH5ysKf9cqb05pbp9fs0W5K2CfPXgJV10Zb/EJvlIFYCWgWAHAAAAQLPh9hj6YNNhdYoJVq/EcBWUVemRD7er1Fmt3olh+u3FXWS1WnT3/+xSJUnXDU7Wo5+ky2qRrh3cRg+M76ywwMazsDEAnAjBDgAAAIBmwVnt1t0LNurrHTnyt1s1sUecPtt2RM5qjyTpkcndTznz5oahbRUR5KtucaHqGMPW3gCaBoIdAAAAAE2WYRj6ekeO3lqfpb05JcrML5ckVbo8en/TYUlSj4RQ/XpMR/VvE3HKa1mtFl3WJ+Gc1wwADYlgBwAAAECjYRiGDhVWaHt2sdpFBalz7IlnzhiGoZV78/W3r3ZpS1ZRrfeeuLynlu3Okd1m1Y3D2mpAmwi27AbQbBHsAAAAAGgUCsqqdO3La7XjSLEkyWKRHpvSXTcMbes9p9Ll1p5jpfpg02G9urJml6sAu00jO0Xpq/Rjurh7rKYNStL0wclm3AIAnHcEOwAAAAAahae+2qUdR4plt1mUEB6gzPxyPfLRdu0+VqJHLu0uXx+rfvf+Nu8jVpJ049A2untMilqH+KuovEqh/nZm5wBoUQh2AAAAAJjuky3ZWrjuoCTpjVsHa1C7SL3w7T499dUuvbHmoHYfK9VjU7rr4y3Z3ja/m9hFd4zs4H0dHuh73usGALMR7AAAAAAw1VvrD+rB97fJMKTpg5M1uH0rSdLdo1PUJTZE9/x3s9ZlFOiSf3wnSeqbHK6XbhigqGA/M8sGgEbBanYBAAAAAFquV1dk6Lfv/Rjq/OmyHrXev6hrjD68e5jaRQV5j900rC2hDgB8jxk7AAAAAM47wzD0zyV79fTi3ZKk20e00+8mdj3h+jgprUO06J4RWpdRIGe1R2O7tj7f5QJAo0WwAwAAAOC8e3PdQW+oc+/Yjrrnoo6nXPTY327TyE7R56s8AGgyeBQLAAAAQIP7aPNhvfDtXhmGcdx7x4orNfvznZKk+8Z10r1jO7GTFQCcIWbsAAAAAGhQzmq37vnvZklSn8RwDUuJkiRtzirS+owCLd2VoxJntXonhunu0SkmVgoATR/BDgAAAIAGtT272Pv1mv35KnFW6+Xv9mt9ZqH3uNUiPXFFT9mszNQBgLNBsAMAAACgQW06WOT9+tkle71f220WRQX76YijUrePaK/u8WEmVAcAzQvBDgAAAICz4vYYMgxDPraaJTw3HSw87pxfXNhBNw1rq7AAu3YcKVafpPDzXCUANE8EOwAAAADO2IH8Ml354irllVbJbrPI38emcpfb+77NatG/r+uvsd1ivMf6JkeYUSoANEsEOwAAAADOiGEY+sPH25VXWiVJcrkNudzVkqTIIF8tumeEXG6PEiMCzSwTAJo1gh0AAAAAZ+TjLdn6dleu7DaL3v/FcEWF+Kqiyq1Kl0cJ4QEKC7SbXSIANHsEOwAAAADq7aijUg99mCZJmnFhinomshAyAJjBanYBAAAAAJqehesOqqSyWr0Tw/SrMSlmlwMALVa9gp20tDQNHDhQERERmjlzpgzDOG2bZcuWqWvXroqKitKcOXNqvfe3v/1NMTExCg0N1ZVXXqn8/Pz6VQ8AAADgvCpzVmtfbqk+3pItSbpxWFvvblgAgPOvzn8CO51OTZ48Wf3791dqaqrS09M1b968U7bJzc3VlClTNG3aNK1evVoLFizQ0qVLJUnLly/Xf/7zHy1fvlwbN25UZWWl7r///rO6GQAAAAANb29Oqe58PVUjn1yq7n/4Uhc9vUwZeWWy2yy1drsCAJx/dQ52Fi1aJIfDoTlz5qhDhw564okn9Morr5yyzYIFCxQXF6eHH35YHTt21COPPOJts27dOk2cOFGdO3dWSkqKpk2bpt27d5/d3QAAAABNQHp2sbIKys0uo07cHkO/eGODvtx+TAe/r9nHapEkje8Wq1B/FkgGADPVefHkLVu2aMiQIQoMrNmqsFevXkpPTz9tmzFjxshiqfmDf9CgQZo1a5YkqUePHvrlL3+pO++8UyEhIXrllVc0bty4U17P6XTK6XR6XxcXF0uSXC6XXC5XXW/FdD/U2pRqbi7oe/MxBuZjDMzHGJiL/jdXS+1/wzC8fydel1mg615Nld1m1RNTu+uy3nHn/PNLKqv1ydYjcnsM2awWWeXRzlyLqjYdkp/dRz5Wq3xsFvlYLd//v1WZ+eWqcnsU5GvTnpxShQX46NlreqtzbIh8bVat2pevIe0jW9xYNpSW+rPQmDAG5qL/T6+ufWMx6rJQjqT7779flZWVev75573HoqOjtXv3bkVERJywzZVXXqkhQ4Zo5syZkqSysjLFx8fL4XBIki655BJ98cUXkqSBAwdq2bJlCggIOGkNjz76qB577LHjjr/55pvewAkAAABoTPY4LHpll1VjEzy6MM7Q7C025VZavO+PifcoOdjQ9kKLAmzSZW088mnAJWs8hvTvHVbtdJzZRe0WQy7DoklJbo1PrNOvDgCABlBeXq7p06fL4XAoNDT0pOfVecaOj4+P/Pz8ah3z9/dXeXn5SYOd/23zw/mS9Pbbb+vAgQPauXOnoqOj9cADD+i6667Te++9d9IaZs2apfvuu8/7uri4WElJSRo/fvwpb7KxcblcWrx4scaNGye7namr5xN9bz7GwHyMgfkYA3PR/+Zqaf1f5qzWk/9cpQp3pbaUBmtSh87KXbtZrYJ8NbVPnF5ZeUBLsmsHLkN6d9btF7Q77lpV1R59uu2IBraNUFJE3f9R8+UVmdrp2C0/H6tGd46W22PIVe3W0ZxchUVEyiOLqt0eVXsMudyG3B6Pqt2GMvJr/t7uMiwK9LXp8RtGK4THrhpMS/tZaIwYA3PR/6f3w1NKp1PnYCcyMlJpaWm1jpWUlMjX1/eUbXJzc094/sKFC/WLX/xCnTt3liQ988wzCgsLU1FRkcLDw094PT8/v+PCJUmy2+1N8huhqdbdHND35mMMzMcYmI8xMBf9b66W0v//+GK3DhdVSpIOFlTo7Y01O0lN6hWnhyf3UO/kSP3m3S1yVnvUKshPeaVOvbgsQ51jwxTk5yNntUdWizS0fSv95cudemPNQUUG+Xq3F3d7DA1qF6leieGSah75yi11qtzpVllVtXYdLdHTi/dIkv4wubumD06WVPML1eeff66JEweddBzyS50aOnuJqqo9uqp/oiJDmCF/LrSUn4XGjDEwF/1/cnXtlzoHOwMHDtTLL7/sfZ2ZmSmn06nIyMhTtlm4cKH39ebNm5WQkCBJqq6u1rFjx7zvHTlyRJLkdrvrWhIAAADQaG04UKh5qzIlSZFBviooq9KSnTmSpNGdW0uSpvSOV/82Eaqoqla7qGBNfm6F0o8U69b/pNa61uB2kVqbUSBJKiir0mOf/LjWZZCvTct+M1oH8sv14HtbtSen9LhaJvWM07RBSfWqv1Wwn/5vbCd9tPmw7hjZvl5tAQDnT52DnZEjR8rhcGj+/Pm64YYbNHv2bI0dO1Y2m03FxcUKCAg4Lk2aMmWK7r77bi1dulQjRozQU089pQkTJkiShg8frjlz5igxMVEBAQF65plnNHToULVq1aph7xAAAAA4z5zVbj343lYZhnRFvwS1DvHXv5btkyT5+Vg1pP2Pf+dNCP9xjcl5twzUP77eoxV78+Rjtchus2rn0RJvqHNlv0SF+PvoWHGlbFaLthwqUlZBhX755kZtzipSpcsji0UK8vVRoK9NkUG+Gt2ltX45OsW7eHN9/OLCDvrFhR3OsjcAAOdSvdbYmTt3rqZPn66ZM2fK7XZr2bJlkmp2yHrmmWc0derUWm2ioqL09NNPa8KECQoLC1NQUJB3u/N7771X2dnZevzxx5WXl6ehQ4eedvt0AAAAoCl4Yek+7ckpVasgXz08qZsy88v07+X7vg96EhXgazthu9Yh/vrz5T1rHbvz9VR9uf2YusSG6IkresjP58e2K/fm6dqX12rN/prgZ3C7SM29foDCAnmsAQBaijoHO5I0depU7dmzR6mpqRo2bJiio6Ml1TyWdTIzZszQ+PHjtWPHDo0aNcq7yLG/v7+effZZPfvss2dePQAAANBIHMgv0/LduWofHawXvt0rSXp0SndFBPkqIshXK347RjaLRTGhx68ZeSqzr+ilbnEH9LMBibVCHUkanhKlWZd00XNL9irIz6Znp/Ul1AGAFqZewY4kJSQkeNfJqauUlBSlpKTU96MAAACAJsEwDN32n9Ra69uM7dpal/aK877+6SNX9RER5Kt7xnY86ft3juqgG4e1lccwFOhb77/eAwCaOP7kBwAAAM7St7tzjwt1/nplrzNa1+ZM+NtP/GgXAKD5I9gBAAAAzkJReZX+uminJOmmYW1116gOig3zN7kqAEBLYTW7AAAAAKCpyit16udz12jn0RJFBvnqzlHtCXUAAOcVM3YAAACAM3DUUalrX16jfbllig7x05u3DVZc2JmtowMAwJki2AEAAADqqarao+teWat9uWWKD/PXgtuHqF1UkNllAQBaIIIdAAAAoJ4WrjuovTmligr201t3DlVSZKDZJQEAWijW2AEAAADqweX26LkleyRJ/zeuI6EOAMBUBDsAAABAPezNKVVeaZVC/Hx09YAks8sBALRwBDsAAABAPaQddkiSusWHym7jr9MAAHPxXyIAAACgHrZnF0uSeiSEmVwJAAAEOwAAAEC9bM+umbHTIyHU5EoAACDYAQAAAOrM4zF+nLETz4wdAID5CHYAAACAOlq2J1flVW6F+PmofXSw2eUAAECwAwAAANTVi0v3SZKmDU6WzWoxuRoAAAh2AAAAgDrZm1OidZkFstssumV4O7PLAQBAEsEOAAAAUCdr9hdIkga2jVRsmL/J1QAAUINgBwAAAKiD1Mwfgx0AABoLgh0AAACgDtZnFkoi2AEANC4+ZhcAAAAANFaGYWjjwUJ9uClbh4sqZLNa1Dc53OyyAADwItgBAAAA/oej3KVnvtmtr7Yf0+GiCu/x0Z2jFeTHX6EBAI0H/1UCAAAA/scbaw/otZWZkqQgX5smdI/V5D7xGpESZW5hAAD8D4IdAAAA4H9sOlizns74bjF6dlpf+dttJlcEAMCJsXgyAAAA8BOGYWhzVpEk6c5RHQh1AACNGsEOAAAA8BOHiyqUV1olH6tF3eNDzS4HAIBTItgBAAAAfmJLlkOS1DUulNk6AIBGj2AHAAAA+Ilvd+VIkvokhZtbCAAAdUCwAwAAgGZt19ESFVe6ah2rdLl1239SNfLJpTpWXCmpZm2dzLwyvbfxkCRpat/4814rAAD1xa5YAAAAaHaqqj16fc0B5Zc69cK3+xQX5q+Pf3mBokP89Nw3e/Sf1QeUV+qUJD368Xa1jQrSF2lHlZFXJknqFheqfskRZt4CAAB1QrADAACAZufzbUf0+Kfp3tdHHJX61cKN+ttVvfX04t21zl2UdrTWax+rRb++KEUWi+W81AoAwNkg2AEAAECzs+FAoffrLrEhyioo15r9BbrptXWSpKhgX31z34Wa/cVOfbolWyM7ReviHrG6sHO0/O022W2sWAAAaBoIdgAAANDsbD1UJEm6b1wn3TGyvZbszNGMBRu1L7fmUatbL2ivsEC7/nJFT/3lip4mVgoAwNnhnyIAAADQrFRVe7TjSIkk6bI+8fK32zSxZ5zuHNnee864bjFmlQcAQINixg4AAACalZ1Hi1Xl9ig80K7kyEDv8ZkTOqvS5VaAr49SWgebWCEAAA2HYAcAAADNyoq9eZKknglhtRZA9rFZ9dhlPcwqCwCAc4JgBwAAAM2CYRgqq3Jr/qoDkqTJveNNrggAgHOPYAcAAABN2qsrMvTskj1yVLhkGDXHokP8dFkfgh0AQPNHsAMAAIAm6+3ULP3x0/Rax3ysFt0/rpP8fGwmVQUAwPlDsAMAAIAmqbjSpT9/tkOS9IsLO+jmYW0V6OejALtNNqvlNK0BAGgeCHYAAADQJM1dtl+OCpdSWgfrgfGdCXMAAC2S1ewCAAAAgPpavS9fLy7bJ0m6f1wnQh0AQItFsAMAAIAm59GPt8vtMXRF3wRd3CPW7HIAADANj2IBAACgUTMMQ/9atl8VLrfuGNleReVV2nWsRFaL9MjkbrJYmK0DAGi5CHYAAADQaFVUuZV6oEB//WKnJOnd1CwN6dBKktQvOULhgb5mlgcAgOkIdgAAANAoFZRVafRT38pR4ZIk2W0WZTsq9f7Gw5KkUZ2izSwPAIBGgTV2AAAA0CilZhZ4Qx0fq0WL7hmpO0e2l9UiWS3S2G4xJlcIAID5mLEDAACARmnn0RLv13Nv6K+U1sGaNbGrrh6YpOIKl7rGhZpYHQAAjQPBDgAAABqlHUeKJUm/n9hVY7r8ODunQ3SwWSUBANDo8CgWAAAAGqUfZuwwMwcAgJMj2AEAAECjU15Vrcz8MklS17gQk6sBAKDxItgBAABAo7M5q0iGIUWH+KlVsJ/Z5QAA0GgR7AAAAKDReXt9liRpdGe2NAcA4FQIdgAAANCo5JRU6vNtRyVJ1w1pY3I1AAA0bvUKdtLS0jRw4EBFRERo5syZMgzjtG2WLVumrl27KioqSnPmzDnhOT//+c/1q1/9qj6lAAAAoBmqdLk1442NqnJ71DsxTL0Sw80uCQCARq3OwY7T6dTkyZPVv39/paamKj09XfPmzTtlm9zcXE2ZMkXTpk3T6tWrtWDBAi1durTWOV9++aWWLFmixx9//IxuAAAAAM2Dx2No5rtblXqgUCF+Pvrbz3qbXRIAAI1enYOdRYsWyeFwaM6cOerQoYOeeOIJvfLKK6dss2DBAsXFxenhhx9Wx44d9cgjj9RqU1FRoRkzZmj27NkKDw8/45sAAABA0/f04l36ZEu2fKwW/ev6/uoUw25YAACcjk9dT9yyZYuGDBmiwMBASVKvXr2Unp5+2jZjxoyRxWKRJA0aNEizZs3yvv/444+roqJCPj4+WrJkiUaPHu0990ScTqecTqf3dXFxsSTJ5XLJ5XLV9VZM90OtTanm5oK+Nx9jYD7GwHyMgbnof3OdqP8Nw9C/lmfo+aX7JEmPX9ZNg9qEMUbnED8H5mMMzMcYmIv+P7269o3FqMtCOZLuv/9+VVZW6vnnn/cei46O1u7duxUREXHCNldeeaWGDBmimTNnSpLKysoUHx8vh8OhgwcPqlOnTho0aJDGjx+vDz74QMnJyXr//fdPGu48+uijeuyxx447/uabb3oDJwAAADQNhiF5JC3JtujTgzZJ0oREjyYmecwtDACARqC8vFzTp0+Xw+FQaGjoSc+r84wdHx8f+fn51Trm7++v8vLykwY7/9vmh/Mlad68eYqJidHixYvl5+ene+65R23atNHixYs1fvz4E15v1qxZuu+++7yvi4uLlZSUpPHjx5/yJhsbl8ulxYsXa9y4cbLb7WaX06LQ9+ZjDMzHGJiPMTAX/W8eZ7VHa/bl6oNlG1Xm31pbs4tVUPbjv0Y+eHEn3Tq8rXkFtiD8HJiPMTAfY2Au+v/0fnhK6XTqHOxERkYqLS2t1rGSkhL5+vqesk1ubu4Jzz906JAuuugib/ATEhKijh07KiMj46TX8/PzOy5ckiS73d4kvxGaat3NAX1vPsbAfIyB+RgDc9H/51d5VbWueWmdtmcXS7JJyq/1/vCUVrpzVMopH8tHw+PnwHyMgfkYA3PR/ydX136pc7AzcOBAvfzyy97XmZmZcjqdioyMPGWbhQsXel9v3rxZCQkJkqSkpKRaa/R4PB4dOnRIbdq0qWtJAAAAaAJeWr5fL3y7V4XlLoX4+6hjUJUuGdxV/du2UrnTrWW7c3T7iPaEOgAAnIE674o1cuRIORwOzZ8/X5I0e/ZsjR07VjabTcXFxSdc1GfKlClasWKFli5dqurqaj311FOaMGGCJOnqq6/WJ598ovfee0+HDh3SrFmz5HQ6NXz48Aa6NQAAAJgtp6RSf/58hwrLXbJapBem9dGNnTy6aWgb9UuO0AUdo/T7Sd3UOtTf7FIBAGiS6rXGzty5czV9+nTNnDlTbrdby5Ytk1SzQ9YzzzyjqVOn1moTFRWlp59+WhMmTFBYWJiCgoK825137txZb731lh566CHt3LlTHTp00EcffaSQELa1BAAAaC7WZxR6v/7q/0aqTYS/Pt9pYkEAADQzdQ52JGnq1Knas2ePUlNTNWzYMEVHR0uqeSzrZGbMmKHx48drx44dGjVqVK1FjidNmqRJkyadWeUAAABo9NZm1Kylc9OwtkppHcK2tgAANLB6BTuSlJCQ4F0np65SUlKUkpJS348CAABAE+X2GPpmxzHNX31AkjS43cnXZQQAAGeu3sEOAAAAcDKGYWj5njzNXrRTO478uE3rQIIdAADOCYIdAAAANIi0ww79ZdEOrdxb8/hViJ+PBrSN0MhO0YoK9jO5OgAAmieCHQAAANSJ22MoI69UheUuFZW7VFhepapqjzq2Dtab6w7qo83ZkiRfm1XXD22jX45OUUSQr8lVAwDQvBHsAAAA4LRW7s3TIx+laV9u2SnPu6xPvB4Y31lJkYHnqTIAAFo2gh0AAACc0hOf79Dc5fslSQF2m2JC/RQW6KuIQLtKK6u14WChhneI0oOXdFGPhDCTqwUAoGUh2AEAAICX22Poz5/tkCTdOaq9qj2GXvquJtS5aVhb/d+4TgoLsNdqYxiGLBbLea8VAAAQ7AAAAOAnlu/J1asrMyRJb647oG5xoTIMaUj7SD06pfsJ2xDqAABgHqvZBQAAAKDx+HTLEUlSiL+PKl0ebTxYJEn6Wf8kE6sCAAAnw4wdAAAASJKc1W59lX5UkvTKjQNVXOHSP77ZI5vVokt6xppcHQAAOBGCHQAAAEiSFqcfU0lltWJD/TWgTYSsVovGdosxuywAAHAKBDsAAAAtXKXLrbnL92vO4t2SpKsHJMpqZd0cAACaAoIdAACAFu6pL3fp5RUZ3tfXDEo2sRoAAFAfLJ4MAADQgqUddui1VZne1zcObaOE8ADzCgIAAPXCjB0AAIAWZOXePP3j6z164oqeah3qp7vf3Ci3x9CknnF6/tp+ZpcHAADqiWAHAACgBbn+lbXyGNKMBRvUPipYB/LLlRAeoD9f3sPs0gAAwBkg2AEAAGghKqrc8hg1X+8+Vqrdx0plt1n0/LX9FB7oa25xAADgjLDGDgAAQAuReqDguGMPTeqmPknh578YAADQIAh2AAAAWojv9uTVej2pZ5xuGNrGpGoAAEBD4FEsAACAFuCIo0IL1hyQJM25urciAn01PCVKFovF5MoAAMDZINgBAABoovbmlCohPEABvrbTnvu3L3eprMqt/m0iNLVPgqxWAh0AAJoDgh0AAIAmprjSpQ83HdYjH21XqyBf3Tmqva4f0vakAY/L7dHi7cckSbMu6UKoAwBAM0KwAwAA0ARUVXu0P69UK/bk6U+f7fAezy+r0hOf79Tc5fv1+GU9dEnPuOPars8sUImzWlHBvuqXHHE+ywYAAOcYwQ4AAEAjZhiGFqcf058/36ED+eW13hvTpbUu7hGr55bsUVZBhR54Z4su6BilEH+7HvkoTav35Ss2zF+F5VWSpFGdWjNbBwCAZoZgBwAAwESGYUjSCRcxPpBfpt9/kKYVe2vvZjWhe4xuHNZW/ZIj5G+36fK+Cbr4meXal1umDzcd1pD2rTR/dc1CyXtySr3tLura+hzeCQAAMAPBDgAAgEmyiyo09fmVKnNWq110kNpFBatdVJCqqj0K8ffRh5sOa09OqXx9rLrtgna6fmgb7c0p1dD2reRjs3qvY7dZdf2QNnr0k3S9tipTh4sqJUmD2kXqqv6Jyi6qUIDdpgndY826VQAAcI4Q7AAAAJjk+aV7lVPilCSlHS5W2uHi484J9LVp0T0j1KZVkCQpLizghNe6sn+invlmj/bnlulfy/ZJkq4f0kaTe8efo+oBAEBjQLADAABgglV78/RO6iFJ0j9+3keBvj7KyCvV/twyfbDpsJzVHknSZX0SvKHOqYT42/XA+M566MM0SVJcmL/Gdo05dzcAAAAaBYIdAACA86jMWa2/LNqhN9YclCSN6Bily/okfP9uTRDzx8t66NLnvlNmXrluGta2zteeNihZe46VyG0Y+uXojifd/hwAADQfBDsAAADnyap9efrNu1t1qLBCknTdkGQ9eEnX487z9bHq3V8Mk6PcpaTIwDpf32a16LHLejRYvQAAoPEj2AEAADjHypzVmr1op15fU7NTVUJ4gP52VS8NS4k6aZtQf7tC/e3nq0QAANBEEewAAIAmr9LlVnmVW5FBvmaXUouz2q2PN2fr2SV7lFVQM0tn+uBk/W5iVwX78dcwAABw9vgbBQAAaNIMw9ANr67T+swC/XpMR90yvJ1W78/Xl9uPatthhx6+tJtGdYo2pa5fvLFRS3bmSJLiw/z116t6aUTH818LAABovgh2AABAk+Aod+mauavVMyFMf/tZb0k1M2LmrzqgdRkFkqR/fLNH//hmT61297+9WYv/b5SC/X30wtJ9OpBfqv0HrHo/b6OGd4zS7SPay2KxNEiNHo+hF5ftU1ZBubrGhWrJzhz5+lj1q9Epuml4W4XwaBUAAGhgBDsAAKBRMQxDhworlBgRUCtw+WjLYe08WqKdR0t0YefW2nKoSG+tz5KjwiVJatMqUFXVHh1xVCopMkATusXq29252ptTqsc+2a5B7Vrp71/v/v5qVqkgT8v25OlAfrkev6yHrNazC3ec1W7d9/YWfbb1SK3jD4zvpDtGdjirawMAAJwMwQ4AAGhUnvm6ZtbNRV1a65mf9/HOcvki7aj3nLvf3Oj92tfHqq6xIZp/62AF2G3KL3MqNtRfFotFl2YV6YoXVurDzdn6cHO2JGlSj1j5lx5WfLuO+ue3+7Vg7UG53B795Ypesv0k3Fm7P1/vbzyso8WVevjSbkppHXzSmosrXbpz/gat3p9f63hyZKBuGd6uQfoFAADgRAh2AADAOWMYhr7ZkaN5qzJ1oKBMg9u1UttWgbLbrLpz1PGzWLYdcuiFb/dKkr7ZmaOrXlytR6d01z++2a01+wtqnTuyU7RuGtZGF3ZqXWu2TVxYgPfrPknhun1Ee/17+X7vsYcv7aK1yw5p4pgUdWgdqvve3qy3Uw+pqtqj30/qpi+3H9U7qVnacsjhbRO8eLeev7bfCe+xqtqja19aq22HHQrytemF6/rr8U/TtTenVA9f2k0+NuuZdR4AAEAdEOwAAIBz4rOtR/Tckj3aebTEeyyr4JD36z5J4bJZLXptVab25ZRKkvfcnglhOlZcqV3HSjTtpTXeNgPbRujJq3rLZrEouVVgnep4YEJnlVe59fqaA5o+OFmtfrJz1tS+CfKxWXTPfzfXmtUjSXabRT0SwrTpYJG+3H5UuSVORYf4HXf9N9ce0LbDDkUE2vX6rYPVIyFMXW8brKzCcvVvE1nH3gIAADgzBDsAAKDBfZF21Pu4VJCvTdcNbSObxaIXvt3nPefG19ap0uU5ru2ANhGac3Uf2X0sun1+qtIOF6tVkK8eurSrxnSOUVhg/RYgttusenxqD/36oo6KDPKVx11d6/1Le8UrxN+ue/67SUXlLnWKCdbVA5I0tW+CooL9dNnzK7Ulq0h/WbRDT17Zq9YMnDJntZ5dUjPD6IEJndUjIUyS1DrUX61D/etVJwAAwJkg2AEAAA3u/Y01M3Mm947Xny7r4Q1jLkiJUn5Zlf7vrc2qdHnk52PV1D4JMmRo9f58/eHS7hrbLcZ7nbfvHKpPtmRreEqUEiPqNkPnZH6YbeNxH//eqE7RWnL/hcotcapTTHCtRZt/OTpFd7yeqvc3Htb6zAJdP6SNrhmQrLBAu95OzVJBWZXatgrUNQOSzqo+AACAM0GwAwAAGlR5VbWW78mVJN01qn2tGTbDUqIkScH+PjqQV6YpfRIU+ZNHo/5XoK+PrhmYfG4L/l5kkO8JaxnXLUYvXttPD76/TVkFFXri85168otdCrDbVOKsmf1z+8j2rKUDAABMQbADAAAa1PLduap0eZQYEaBucaEnPGd059ZS5/Nc2Fm4uEecRnVqrY82H9a8VZnaebTEG+pEBfvpyn6JJlcIAABaKoIdAABwRlbvy9eKvbm67YL2ivjJTJe3U2sew5rUM67WI01NXYCvTT8flKxrBiZp17GaRZ4z88rUMSZE/nabydUBAICWimAHAACckQff36oD+eV6b8Nh/f2aPhraoZXSDju0ZGeOJOmagc1zzRmLxaIusTUzkX74fwAAALMQ7AAA0IIVlFXpi7Sj8rdbFRHkq+hgP3WPDz3tTJusgnIdyC+XJB0trtS0l9Yo2M9Hpd8/njS0fSu1jw4+5/UDAAC0dAQ7AAC0YH/6NF3vbzpc61inmGANad9K+WVVmtwrXhf3iPW+9/RXu7TpYJGyHRWSpF6JYeoSG6K3Uw95Q53u8aF67LLu5+8mAAAAWjCCHQAAWii3x9CSXTWPTfVvE6FKl1t7c0q1+1jN/yRp6c4c9U2+UDGh/tqXW6rnluytdY0LO0XrvvGddWHn1vp4c7ZuGNrGu/MVAAAAzj2CHQAAWqith4pUVO5SiL+P3rpjiHxsVm075NCTX+5UQniA/rs+S+VVbt3x+gZNG5ik9CPFx11jRKdoSdLEnnGa2DPufN8CAABAi0ewAwBAC/XtrlxJ0oiOUfKxWSVJPRPD9PqtgyVJPx+UrKv/tVpbsoq0JavI2+65aX2VEBGgfTmlGtAm4rzXDQAAgB8R7AAA0EKtzciXJI3oGH3C9/skhevze0bo821H9M3OHG09VKT4sACN6xYjf7tN/ZIJdQAAAMxGsAMAQAtkGIa2Z9c8WtU7Mfyk56W0DtavL+qoX1/UUYVlVfL1scrfbjtPVQIAAOB0CHYAAGiBsgoqVFJZLV+bVR1j6rYteUSQ7zmuCgAAAPVlrc/JaWlpGjhwoCIiIjRz5kwZhnHaNsuWLVPXrl0VFRWlOXPmnPAcl8ulnj176ttvv61POQAA4Axtz3ZIkjrHhshuq9dfBwAAANCI1Plvck6nU5MnT1b//v2Vmpqq9PR0zZs375RtcnNzNWXKFE2bNk2rV6/WggULtHTp0uPOe/LJJ5WWllbv4gEAwJn54TGs7vGhJlcCAACAs1HnYGfRokVyOByaM2eOOnTooCeeeEKvvPLKKdssWLBAcXFxevjhh9WxY0c98sgjx7XZs2ePnnrqKbVt2/aMbgAAgKbMMAyt2penDQcKlV/qrNNs2IawKatQEsEOAABAU1fnNXa2bNmiIUOGKDAwUJLUq1cvpaenn7bNmDFjZLFYJEmDBg3SrFmzap1z55136sEHH9SiRYtOW4PT6ZTT6fS+Li6u+ddGl8sll8tV11sx3Q+1NqWamwv63nyMgfkYA/P9dAw+2JSt37z/46zVID+bkiMClRwZoMt6x+u/qVkqdbr12o39FOjbMEvjHSwo16p9NTtiDWkX3uK+F/gZMBf93zgwDuZjDMzHGJiL/j+9uvaNxajjPw3ef//9qqys1PPPP+89Fh0drd27dysi4sTbnV555ZUaMmSIZs6cKUkqKytTfHy8HI6a5/pfe+01/fOf/9TatWs1duxYPfroo7rwwgtPWsOjjz6qxx577Ljjb775pjdwAgCgKfnXDqt2FFkVYDNU6ZYMWU543tgEjyYnexrkMz/MtGrpEau6hHn0i24Nc00AAAA0rPLyck2fPl0Oh0OhoSefZV3nf/rz8fGRn59frWP+/v4qLy8/abDzv21+OF+qWX9n1qxZ+uKLL+TjU7cyZs2apfvuu8/7uri4WElJSRo/fvwpb7KxcblcWrx4scaNGye73W52OS0KfW8+xsB8jIH5fhiDYSNH64F1KyQZen/GcCVFBCirsEIHCyv05tosLduT523z7RGbbpowSIPbRZ7VZ+eUODVrwwpJbv3f5P4a0zn67G6mCeJnwFz0f+PAOJiPMTAfY2Au+v/0fnhK6XTqHOxERkYet8BxSUmJfH1PvvVpZGSkcnNzT3j+vffeq1tvvVV9+vSpawny8/M7LlySJLvd3iS/EZpq3c0BfW8+xsB8jIH5VmY45HIbahcVpC7x4bJYLOoa6K+uCRHq2yZSE/+xQn4+VnWJDdE3O3P0izc3a+71AzS0Q6sz+ryKKrce/2yXyqvc6pscrvHd47yPS7dE/AyYi/5vHBgH8zEG5mMMzEX/n1xd+6XOiycPHDhQa9as8b7OzMyU0+lUZOTJ/+Xwf9ts3rxZCQkJkmoen3ruuecUHh6u8PBwrVixQpdeeqlmz55d15IAAGiyqj3Ss0v2SpIm9ow9LmBpHeKvpQ+M0lf/N1LPX9tPg9pGqqSyWte/slZvrT9Y789LzSzQxGe/0xfbj8pikR6a1LVFhzoAAADNRZ2DnZEjR8rhcGj+/PmSpNmzZ2vs2LGy2WwqLi4+4aI+U6ZM0YoVK7R06VJVV1frqaee0oQJEyRJGRkZ2rp1qzZv3qzNmzdrwIABevnll3XXXXc10K0BANB4fXvEov155YoK9tUdIzuc8JwQf7uC/Hzkb7dp/q2DNLl3vKo9hn773jY99OE27ThSLI/n1EvlVVS59fin6frZv1crI69MsaH+evWmgerf5uwe6QIAAEDjUK81dubOnavp06dr5syZcrvdWrZsmaSaHbKeeeYZTZ06tVabqKgoPf3005owYYLCwsIUFBTk3e78f7c39/f3V2xsrMLDw8/qhgAAaOyOOCr15aGaf1uZdUlXhQWcfpqtv92mZ3/eRx2ig/TM13v0xpqDemPNQcWH+ev5a/upb/Lx692lZhZo5rtblZFXJkn6Wf9EPXRptzp9HgAAAJqGeu2bOnXqVO3Zs0epqakaNmyYoqNrFlzMzMw8aZsZM2Zo/Pjx2rFjh0aNGnXSRY6//fbb+pQCAECT9ZdFu1Tlsah/criu6JdQ53YWi0X3ju2kLrGhenVlhjYdLFS2o1L3vb1Fi+4ZIX+7TVLNLJ2nvtqlV1dmyDCkmFA/zb6il0Z3aX2ubgkAAAAmqVewI0kJCQnedXLqKiUlRSkpKfX9KAAAmiyX26PC8iqFB/jK1+fHJ59X7MnTou3HZJGhP1x6ZuvcXNwjVhf3iFV+qVMTnvlOGXllem1lpn5xYYfjZulc1T9RDzNLBwAAoNmqd7ADAABOzOX26I75qUo9UKiSympJUlSwn964bZC6xIaqqtqjRz6u2WFyRKyhrnEhZ/V5rYL99NuLO2vmu1v12soM5Zc69cpPZun85YqeGtMl5qzvCwAAAI0XwQ4AoNn5aPNhbc4q0qxLutaaLXOubT1UpKW7cmsdyyt16ubX1uvyvgl64dt9kqSoYF9dklTeIJ85pU+8nvxyl3JKnHp5RYak72fpTOqmsEBm6QAAADR35+9vuwAA1NHB/HKt2JN3Rm2Lyqt0z38367WVmfp4S3YDV3Zq2w45JEkjOkZp08PjtPHhcWofHaQjjkpvqCNJD17cWYEN9E8rfj423Ty8raSaWTqv3jRAT/2sN6EOAABAC8GMHQBAo/L2+izN+mCb3B5DL90wQOO6nfpRokqXW+syCrRqX77aRQWqqNzlfe/zbUd0Vf/Ec12yVu7N0z++3qN1mQWSpH7JEYoI8pUk/efmQbr8hZXKK63SDUPb6OcDk9UxOkCfH97UYJ//i1Ed1DcpQt0TQhXqT6ADAADQkhDsAAAalb9/vVtujyFJ+iLt6EmDneJKl3777lZ9szNHVdUe7/GfrkW8fHeuCsuqvCHLufDp1mz98s3aIU2vxDDv10mRgfr8nhHKKihXv+QIWSwWuVyu/73MWbFYLBraoVWDXhMAAABNA49iAQAajdwSp444Kr2vl+3Olef7kOen3B5Dv3xzkxalHVVVtUexof6KCfWTJBmGFORrU4foIFV7DC1Ye+Cc1ZuZV6bfvLv1uOM9E8JqvW4d4q/+bSLPaAcsAAAA4FQIdgAAjUba4Zo1apIjAxXka1NeqVNp2Y7jzlu1L0/Ld+fK327VW3cM0epZY3TnyA7e9yf0iNWvxnSUJL2yIkNlzupzUu+/l+9XeZVbg9tF6l/X9ZNUszBy61D/c/J5AAAAwP8i2AEANBrbvg92+iWHa2SnaEnSvFWZx5239ftFisd3i9Xg9q1ksVhqPbI1pXe8Lu0Vp7atAlVY7jons3Yc5S59uOmwJOm+cZ10cY84vXTDAL1+6+AG/ywAAADgZAh2AACmen7pXt31+gbNfGeLPtxcE5T0TAzXXaNqZuB8sOmwdh4trtVm59ESSVLXuFDvsaTIQP3iwg66ekCiLkiJko/NqhmjUyRJc5dnqNLlbtC639mQpQqXW11iQzSoXaQkaVy3mFo1AQAAAOcawQ4AwDQbDxbqb1/u0hfbj+qdDYe0P7dMktQnKUy9k8I1sWesDEP6/Qdptdba2XGkJujpGhdS63q/vbiLnryqt3xsNf95u7xvghIjApRX6tTCdQcbrG63x9D81TWzgG4c1pa1cwAAAGAadsUCAJxXLrdHz32zR72TwvXh5mxJ0vCUVhrWIUolldWKDfVTv+QISdJDk7pp2a5cbThQqNfXHNCNw9qq0uXW/txSSTrt7Bi7zapfXNhBv/8gTY99kq4gXx9N7h2vAF/bWd3Dst05OlhQrlB/H03tk3BW1wIAAADOBsEOAOCcyCoo1+trDui2C9rVWkz49dUH9OySvZIkm7VmpsvvJnZV9/iw464RHx6gByd21cMfpumvX+zUmC6t9e6GQ/IYUmSQr1qH+J22jqv6J+q5b/bqaHGlfvPeVn2x/aheumGA97PPxLxVNbN1rhmYdNYhEQAAAHA2eBQLAHBOPPxRmuYu368bXl0nw/jxMaq3U7O8X7s9hjrHhJww1PnBtYOSNahtpMqr3Brx5FL945s9kqQ+SeF1egTKz8emR6d0U1xYTbi0ZGeOnv5q15nelvbllmr57lxZLNL1Q9qe8XUAAACAhkCwAwBocIVlVfp2V66kmoWOP916RJL0xpoD3oWPfzC0Q6tTXstqtWj2lT1rHbtpWNvjjp3KxT3itHrWRfrHz/tIkl74dp8+3Zpd5/aSVO32aOfRYs16f5sk6aIurZXcKrBe1wAAAAAaGo9iAQAaVFF5lWa+u7XWsRe/3ae0ww79e/n+484f0v7UwY4ktY8O1u8mdtETn+/UlN7x+sPkbme0YPFlfRK0PbtYc5fv18x3tiopIlC9k8JP284wDN3z1mZ99n1A5edj1b1jO9X78wEAAICGxowdAECD2Zdbqsn/XKGvdxyTJN0/rpP8fKxKP1LsDXX+b2wn78wZSRr8/Vbhp3P7iPb68t6R+vs1fc5qF6rfXtxFIzpGqcLl1lX/WqWnvtzl3QrdMAzd9/Zm3fX6hlrbo7+dmuUNdawW6amf9VaPhJM/PgYAAACcL8zYAQA0iPWZBbp9fqqKyl1KigzQPRd10pX9EpRVWK63Uw/J12bVX6/qqcv7JqrUWa1ucaHqEheiiCDfOl3fYrGoc2zI6U88DZvVon9O76cH3tmixenH9M+le/Xp1mz9/Zo+kqT3Nx6WJN3/9hbNmthF0SF+evqr3ZKkBy/pojtHtmd7cwAAADQaBDsAgLO2aNsR3fPWZlVVe9QnKVyv3DhArYJrdqy6f3xn2axWXdU/Qf3b1MzOCfbz0ef3jDCt3rAAu166YYC+SDuqRz/ersz8cv36v5s0tmuM95zPth3RZ9uOKKV1sHJKnIoN9dctw9sR6gAAAKBR4VEsAMBZSTvs0D3/rQl1xneL0cLbh3hDHUmKCfXXX67o6Q11GpOLe8Tqy3tHysdqUVZBhd5NPSRJum5Isoa2byWLRdqbUypJunl4W/n68J9NAAAANC7M2AEAnBFntVuOCpdmLNioKrdHY7vG6MXr+stmbVozWsIC7eoWH6qthxwqcVYrLMCuRy7tLl8fqw4XVejDTYdVVF6lG4e1NbtUAAAA4DgEOwCAequocmv8M8uUVVAhSUqMCNDTP+vd5EKdH/RLjtDWQw5J0iU9Yr0zcxLCA3T36BQzSwMAAABOiTnlAIB6+3L7UW+o42uz6oVr+yks0G5yVWeuX5sI79dTesebWAkAAABQP8zYAQCcVrXbo38t26cSZ7Wigvz0ydZsSdKknnF6YEJntYsKMrnCszOkfaSCfG2KCfXX4PatzC4HAAAAqDOCHQDAaX2VfkxPfb/l9089eEkXJUUGmlBRw2od4q+v7hulALutyT5OBgAAgJaJYAcAcFpr9+dLknolhqldVJAKyqo0PCWqWYQ6P0gIDzC7BAAAAKDeCHYA4Dz4bOsR7TparF6J4bqoa2tZLE1rVsj6zEJJ0p0jO2hSrziTqwEAAADwA4IdADjHPtmSrV8t3OR9/bP+ibpzVAdFBfsqPNDXxMrqprjSpZ1HiyVJA9pGnOZsAAAAAOcTwQ4AnENphx2a+e4WSVJUsK/yy6r0zoZDemfDIUlSl9gQjewUrZEdozWgbYT87TYzyz2hDQcK5TGk5MhAxYT6m10OAAAAgJ8g2AGAM7Qlq0gvr8hQQniAOscGq3NMqLrGhSjbUakbX12ngW0jtHx3nipdHo3qFK1XbxqodRkFevLLndqSVSSPIe08WqKdR0s0d/l+BfradEW/BKVEB2tirzi1Dql7iFJR5VZatkO9E8Pl62Nt0Pv8aNNhSdKIjlENel0AAAAAZ49gBwDOQLXbo/97a7P255XVOn736A46XFihvTml2ptTKklqFxWkZ3/eVzarRUM7tNIHM4bLMAwVlru0Ym+elu/O1fLducopceqNNQclSd/tydMrNw1URZVbb6w5oFdWZKhLXIhevXGgrCfYtemxT7brv+uzlBwZqJdvHKBOMSENcp+OCpcWpR2VJP1sQFKDXBMAAABAwyHYAZoZwzBkGDrhL/9oOG+nHtL+vDJFBNp1aa94bc92aOPBIj2/dF+t84L9fPTSDf0VFmivddxisSgyyFdTesdrSu94GYahDzYd1pNf7NLR4kot2ZWj577Zo/lrDii3xClJOlpcqWvmrtb1Q9tqSu9477Wqqj36dOsRSdLBgnLd//YWfXj38AbZtvvjzYflrPaoc0yIeieGnfX1AAAAADSshp2vD8B0T3y+Q50fXqRHP94uZ7Xb7HKapYoqt575erck6VdjOurxqT307l3DFPuT9Wem9onXvJsH6pNfXaCU1qefPWOxWHRFv0St+d1FGp7SSoYhPb14t3JLnEoID9CE7jGSanan+vXCTUo77PC2XZuRr1JntSQpxM9H2w479OSXO2UYhqSaxY/dHqNe91heVa2lu3I0b1WmJOnqgUlNbicvAAAAoCVgxg7QjBSWVeml7zIkSfNWZcrfbtODl3QxuarGrai8SnOX769Z26YOAYwkvboyQzklTiVGBOjaIcmSamZI3XJBWz3x+U4lhAfosct6KCzAfporndjtI9pr1b58xYT465djUnT1gCRVezya/tJabc4qkiT98ZN0tYsK0uasIu06ViJJ+vnAJPVvE6GZ727Vv5ftl9Pl0eTe8Zo2d41GdorS3OsH1Gkm19KdOXrowzQdLqqQJFks0uV9E87oXgAAAACcWwQ7QDPy3sZDtV6/uiJD1w5OVlJkoEkVNX4vLtunfy/br7dTD+mDGcPq1Ffvfr+j1T0XdZSfz4+7WN08vJ2C/Hx0YefWZxzqSNKFnVtr9YMXKSLI7r2+r6z68O7hSjvs0KXPrdC6zAKtyyyo1e6Kfoka1C5SlS63Hv5ou+atytRb67NU5fbo6x05+s/qTN08vN1JPzenpFKPfZKuz75/rOsHE3vGKTKo8W/LDgAAALREBDtAM7HnWImeX7pXkvSnqT20KO2IVu7N198X79aca/qYW1wj4vEYKq50KTzQV4Zh6PNtNSFGXqlTN762Tu/dNUwRpwgxsgrKlZFXJpvVogk9Ymu9Z7dZde3gNg1SZ2zYiXfE6pEQpl9f1FGbDhaqZ0KY+iSFq310sIL9fLxtrh/aVoG+Ppr57hZVuH58HO+Fb/fpxqFtj7umx2No4fqDmr1op0oqq2WzWnTL8La6cVhbrdqbr4t7xh7XBgAAAEDjQLADNFLbsx3682c7dEW/RF3ZL6HW+iaGYdR6/d2eXP1q4SYVlbvUOzFMV/VPVO/EcE3+5wp9sPmwZozuUOfHjJq733+4TW+tz9LLNw5QVkGFsgoq5G+3KjLQV/tzy3Tb/FQtuG2w/O22Wu1cbo/mLt+vv325S5LUNylcof5nPivnbNw3rtNpz7myf6ICfW167JN0XTs4Wf9atk+5JU5tzy5Wl5gfZyXtPlai372/TakHCiVJvRLD9MTlPdUjoWah5KsHMtsLAAAAaMwIdoBG6r/rsrRqX75W7cvX62sO6NYL2umSHrE6XFih6S+tUUpMiObdNFD/Wr5PT325Sx6j5pfyeTcPkr/dpp6JYRrfLUZfpR/T37/eo+en9zP7lky3Zn++Fq7LkiTdMi/Ve3x059b6v3GddNWLq7ThQKGumbtGsy7pIpvVovAAu3x9rLrnv5u969tI0oiO0ee7/Hq7pGecLu4RK4vForRsh77cfkxLduaoS0xbuTzSnK/36OUVmXK5DQX52nT/+M66cVjbBtlNCwAAAMD5QbADNDLHiiv1yZZsbTlU5D22JatIv164SdEhfnJUuFRV7VG2o1Ld/vCFKl0eSdLVAxL1x8t61Jppct/4Tlq845g+23pEvxxdrK5xoef7dhoNl9ujP3y0/bjjF3aO1r1jO6lTTIheumGAbp63XluyivTzuWskSXabRb42q8qq3Arx91FUsJ8OFpTrkibyeNIPM7tGd26tL7cf0+fbjqhnQrBmb7Epr7Jmoe2xXWP0x8u6Kz48wMxSAQAAAJwBgh2gkbn636t1IL/c+/o/twzS5oNFen3NAeWWOGudW+nyyG6z6LEpPTRt0PHbUXeJDdWknnH6dOsRzVm8Wy/dMOC83ENj9J9Vmdp1rEQRgXbNmthVC9cd1H3jOtWaeTO4fSstfeBCPbdkj/67LkvVHkMutyGX261BbSM155reig31V1GFS1HBfibeTf2N6xajP322Q7uOleiW/2yUZFFMiJ8eu6y7JnSPZStzAAAAoIki2AEakQ0HCmuFOjarRYPbRWpUp2jddWF7fbsrV26PoS6xIbr632vkMQzNvb6/BrSNPOk17x3bSZ9vO6LF6ce0Yk+eFqcfVb82EZrSO75Z/jKfX+rU26mH1C4qSBd/v7hxTnGlnvl6jyTptxd30dUDknT1gKQTto8J9defpvbUrEu6ymqx6L2Nh2RImj4o2fuIUlMLdSSpVbCf5lzdW3e8vkEWi3RBa4/+cdswRYawhg4AAADQlBHsAI3I3OX7ar1uFeTrfbTKz8emCd1/fPznm/tHyd9urbXd9omktA7W1L4Jen/jYV33ylpJ0n9WH9CHmw7rFxemaGDbiGYR8OQUV2ru8v1asPagKlxu2awWLf/NaCWEB2j2FztV6qxW76TwkwY6/yvIr+aPx+uGNMwuV43B+O6x+mDGMPlaDe3d8J1CTFr8GQAAAEDDIdgBGonsogotTj9W61h+WdVJzw8LqPsv5b+Z0EVfpx9TcWW199jSXblauitXfZLCdefI9hrfPbZJLpqbVVCuB97ZotQDhXJ7DEmSr49VVdUezV+VqbvHpOiTLdmSpEcnd5O1Cd5jQ+qbHCGXy6W9ZhcCAAAAoEFYzS4AQI2F6w7KY0hD2kfqmu9nldw//vTbWtdFbJi/Xr91sHonhWv2FT215P5RmjYoWb4+Vm3OKtIvFmzUVf9apapqT4N83vlS5qzWbf9J1dqMArk9hga0idB/bhmkF77fAezNtQc1f1XNrk8prYPVNznC5IoBAAAAoGExYwdoBKqqPd5tuK8f0lbjusVoYq84De/QqsE+o3dSuD66e7j39V+u6Kn7xnXS/NWZem1lpjYdLNKHmw7r6oEnf1TJUeHSst25GpESpYggX63Zn6//rMpU/zYRCg2wK9jPRxN7xjVYzafzTmqWdh0rUesQPy28Y4g6RAdLkjweQ32Tw7XpYJGe+mq3JOni7k1jFysAAAAAqA+CHaAR+HL7UeWVOhUd4qfx3WNkt1k1qlP06RuepegQP90/vrNC/e368+c79Py3e3Vl/8QTPpK1dGeOfrVwk0qd1eoUE6yoYD+t2pcvSVqUdtR73trfXaSYUP9zXrskrc0okCTdNLytN9SRJKvVon9O76fL/rlCeaU1j7M1le3JAQAAAKA+eBQLaAReX3NAkjRtULLstvP/Y3ntkGSF+PvoQH65thwqqvVeVbVHS3fl6O43N6rUWbNGz+5jpVq1L192m0XJkbV3VfphPZtzzTAMrc+sCXYGnWBXsITwAH1x70j95YqeevHafuoeH3Ze6gIAAACA84kZO4DJdh0t0bqMAtmsFk0bVLcdmxpaoK+PLkiJ0qK0o/p2V66+Tj+mjzZnq6i8SmVVbu95F6RE6YEJnfXIR2nqHh+mX45JUWlltS597ju53DULF3+yJVu3jWh/zmvOyCtTXmmVfH2s6pl44tAmKthP0wYln/NaAAAAAMAsBDuAyd74frbOuK4xigsLMK2O4d8HO89+s+e49/ztVk0f1Eb3je+kYD8fffzLC2q9/9mvR8jp8uiy51doyyGHsosqFB9+bu/lh8ew+iSGn3bLdwAAAABorgh2ABO5PYY+2Vrz6NK1Q8ydWXJBSpT3a6tFevrq3uqbFKGIQF+F+PuccpvwTjEhkqReieHanFWkFXvzdPWAczv76KPNh2vq7hh1mjMBAAAAoPlijR3gPDjqqFRRedVxx9Ozi1VU7lKwn4+Gtm+4HbDORJtWgeoSGyIfq0Wv3DhQl/dNVNuoIIUF2k8Z6vzUiO9DlpV7885lqcrIK9Oa/QWyWKSr+iee088CAAAAgMaMGTvAObb1UJEuf2GV3B5DXWJDNLhdpAa1a6VB7SL13d5cSdKQ9q3kY8KiyT9lsVj01h1DVeJ0KTEi8PQNTmB4SpSeW7JXK/fmKb/UqVbBfg1cZc0spyc+3yFJGtUp+pw/8gUAAAAAjRnBDnCOLVx3UG5PzcLCO4+WaOfREv1ndc26Or4+NWHOiEbyOFFYoF1hgfYzbt83OVyh/j7KK63S8L8u0bRBybpjZHvFhQXI4zGUmV+mhFDfs6rxL5/v0OL0Y/K1WfXrizqe1bUAAAAAoKmr1xSBtLQ0DRw4UBEREZo5c6YMwzhtm2XLlqlr166KiorSnDlzar03d+5cxcXFyW63a/z48Tpy5Ej9qgdM5PYYqnS5T3lOpcutT7fWfF//c3pfvXBtP904tI26xNasSVNV7ZHVIo3sFH3O6z0f/HxseuWmgeqZEKZKl0evrczUhX/7Vp9sydYz3+zRmKeX6cZ5qSpxndn156/O1MsrMiRJf/tZL/VLjmjA6gEAAACg6alzsON0OjV58mT1799fqampSk9P17x5807ZJjc3V1OmTNG0adO0evVqLViwQEuXLpUkrVixQg8//LBef/11ZWRkqLKyUg888MBZ3QxwLlS63HJWHx/g3DE/VUP/8o2OFVeetO3CdQdVUlmtuDB/TewRp4k94/TYZT30xb0jtfmRcXrphgFaePsQtYsKOpe3cF4NbBupj385XPNvGaQBbSLkrPboVws3eXfbWpNRqLf21f+xs6W7cvTox9slSTMndNZlfRIatG4AAAAAaIrq/NvVokWL5HA4NGfOHHXo0EFPPPGEXnnllVO2WbBggeLi4vTwww+rY8eOeuSRR7xtdu3apRdffFFjx45VYmKibr75ZqWmpp7d3QBnqbyqWlsPFemd1CzNWbxbS3fmaMCfvlbXh7/QY59s955XUunSNztzVFju0lvrs054rb05JfrLop2SpLtGdThuAeLwQF+N6xajwSYvmnwuWCwWjewUrbfuHHrCxY23FVq1Zn/NduU5xZW66bV1en7p3pNez+Mx9MdP0uUxpGsGJGnGhR3OWe0AAAAA0JTUeY2dLVu2aMiQIQoMrFlUtVevXkpPTz9tmzFjxshiqfmFdtCgQZo1a5Yk6dZbb6117q5du5SSknLK6zmdTjmdTu/r4uJiSZLL5ZLLdYbPdpjgh1qbUs1NVV6pUwF2m4L8ar7VT9T3S3bl6s21WbJapRV78+Vyn/gRw9dWZurCjq00rEMrbczM9x7fcKDghGP59vqDqqr2aHiHVpo2IL7FjvfvLu6odzcckiRN6RWnYD+r3lx/WH/6fKc+aBOue/+7Sav2F+jbXbmKCvLRFX2Pn4mzZFeuMvLKFOrvo1kXd1R1dfX5vo1mhT+DzMcYmIv+Nxf93zgwDuZjDMzHGJiL/j+9uvaNxajLQjmS7r//flVWVur555/3HouOjtbu3bsVEXHidS6uvPJKDRkyRDNnzpQklZWVKT4+Xg6Ho9Z5+fn5SklJ0RtvvKFJkyadtIZHH31Ujz322HHH33zzTW/gBEhSdpn05SGrNhdY1TbY0L093LKcYMfuQ2XSM9tschk/vhnsYygu0FBmicV73Gox5DEsivIzdGU7j7LKpM+zbJIku8XQEwPd8rXVvvaTW2w6XG7R9SluDYiu049Zs5VeaNGyIxZd08EjX6v0p002Vbgt6hru0Y6iHycOhtoN/bF/zVgtybYor9KiYTEevb7HpqMVFo2J9+iyNh4T7wQAAAAAzo/y8nJNnz5dDodDoaGhJz2vzjN2fHx85OdXe+tif39/lZeXnzTY+d82P5z/v2bMmKFhw4adMtSRpFmzZum+++7zvi4uLlZSUpLGjx9/yptsbFwulxYvXqxx48bJbj/zHYhwvOIKlx7+OF2fpx3zHssstSi5z3D1TAir1ffl1dLlL66Ry6iQVLND1b0XddDtF7STJN3xxkYt3ZUnSfryngs07eX1yiut0r932mS3WSTVhDUuwyJbm76a2CvO+5l5pU4dXr1MknT3lWPOybbfTclEST+soOVyubQ+92t9eMDmDXXuHNFOL6/MVLFL6nfBGG06WKSPVm+VJK08VnNOVLCvHr9uqFqHtOy+bAj8GWQ+xsBc9L+56P/GgXEwH2NgPsbAXPT/6f3wlNLp1DnYiYyMVFpaWq1jJSUl8vU9+dbFkZGRys3NPeX5r776qpYvX67NmzeftgY/P7/jwiVJstvtTfIboanW3Vh5PIZ+8/5mfbMzRxaLNLFHnIoqqrRyb76u+NdaTekdryev6C5Jstl89Ju3tyirsEKJEQH69FcXKMTfLttP1sH5/aRuSj2wSpf3TVDH2HB9ee9I/WvZPs1ffUDO6ppZI6M7R2vprlzNW31Ql/dLksVikaPcpT8v2i1J6pEQqtiI4PPfGY3ciFhDm0sDlZlfLrvNoltHttfyvfnacaRY3+zK098X7651fmyov+be0F8JkfRlQ+LPIPMxBuai/81F/zcOjIP5GAPzMQbmov9Prq79UudgZ+DAgXr55Ze9rzMzM+V0OhUZGXnKNgsXLvS+3rx5sxISflw/Y926dbr33nv1ySefKCYmpq6lACf0xtoD+mZnjnx9rFp4+xD1bxOhJTuPaeXemvVwPt6SrR7xIYqR9MKy/VqyM0d+Plb967r+Cg88PqBMaR2irX8Y710jqlWwn34/qZtuG9Fer6zIkI/VolsuaKfhs5do6yGHNh4sVO/EcN3xeqrWZtQsDDx9UJvzdv9NiY9VemRSF93xxiZNG5Ss1iH+6pUQph1HivWnz3bI7THUOylc7941VG6PIbvNWit0AwAAAADUqPOuWCNHjpTD4dD8+fMlSbNnz9bYsWNls9lUXFx8wkV9pkyZohUrVmjp0qWqrq7WU089pQkTJkiSjh07psmTJ+u3v/2t+vfvr9LSUpWWljbQbaGlOeqo1JNf7JIk/e6SLurfpubxwJEdo3X9kDbytdV8q//96z1al2vRs0v3SZL+NLWHeiSEnfS6lhMszBMT6q/fTeyq31zcRVHBfrqkR6wk6av0Y3ryy11am1GgIF+bFt4+RNMHJzfofTYnIzpGaeMj4/To5JpZVD0Ta8bB7TEU5GvTP67pI7vNKn+7jVAHAAAAAE6izsGOj4+P5s6dq7vuuksxMTF69913NXv2bEk1O2R99tlnx7WJiorS008/rQkTJiguLk5paWl66KGHJEkLFy5UTk6OHnroIYWEhHj/B5yJN9ceUKmzWn2SwnXD0Lbe4z42qx6f2kM7H79YvRLDVOHyaMFemwxDmj44WT8bkHTWnz26S2tJ0sK1BzV3+X5J0lM/662hHZrfNuYNLdTf7t0GvlfijwHbo1O6q21UkFllAQAAAECTUedHsSRp6tSp2rNnj1JTUzVs2DBFR0dLqnks62RmzJih8ePHa8eOHRo1apR3keN7771X99577xkXDvzUhoOFkqSrByR5g4Kfslotunt0iu58fYMkqVdCqP4wuVuDfPaIjtGyWKTiypotuO8c2V6X9Iw7TSv8rx7xYbp+SBtFBPnqqv6JZpcDAAAAAE1CvYIdSUpISKi1Tk5dpKSkKCUlpb4fBdSJ22NoS5ZDktQ3Ofyk543rGqPB7SK0J7tAz/28t/x8bCc9tz4ig3zVOzFcm7OKNKR9pGZO6Nwg121prFaLHp/aw+wyAAAAAKBJqXewA5xrJZUuTX1+pcIDfXXnyPYa2zXmhLNwfrAnp0SlzmoF+drUKebkj/NZrRa9cctAffrZ54oPD2jQmh+d0l2fbMnW3aNT5GOr8xOOAAAAAACcFYIdNDqbs4q0L7dMUpnueH2DOsUEa9bErhrdufUJz990sEiS1DspvE6L7J6LdXj7JIWrT1J4w18YAAAAAIBTYGoBGp1DhRWSpNYhfgrx89HuY6W6c/4G5ZRUnvD87dk1j2H1Sgw/XyUCAAAAANAoEOyg0XBUuOT2GDr8fbAzvnuMVs4aoy6xIapye/TtrtwTtsvMK5ckdYhmFyUAAAAAQMtCsINGYV1Ggfr+8Ss9+eVOHSqsCWoSIwIV6m/XxT1iJUnf7Dh2wrYZeWWSxPbYAAAAAIAWh2AHjcL7Gw/JY0ifbjnifRQrMaJmgeOLusRIkr7bk6fsoopa7ZzVbmU7ao61bUWwAwAAAABoWQh2YDrDMLR0V44k6XBRhVIPFEqqmbEjSd3jQ9U+OkjlVW5d+eIqOSpc3rZZBeUyDCnI16aoYN/zXzwAAAAAACYi2IHpdhwp0bFi53HHE77fktxqtWj+LYOUFBmgI45KvZOaJcMwJEkZ36+v0zYqSBbLOdjuCgAAAACARoztzmG6H2br/JSfj7XWDJzEiEDNuDBFs97fpj99tkN//WKnusWFysdWk02yvg4AAAAAoCVixg5M9+33wc6FnaO9x9q2On4GzmV94hXiX5NFutyGthxyaMP3j221Y30dAAAAAEALxIwdmMpR7vKGM49f1kPrMgq0PbvYuxPWTwX6+uiFa/tp7f4CXdwjVvtyS5WaWaickkr9fFDS+S4dAAAAAADTEezAVMv35MpjSB1bByspMlBJkYG6sv/Jzx/RMVojOtbM7OmREKbL+iScp0oBAAAAAGh8eBQLpvphfZ3RXVqbXAkAAAAAAE0PwQ5M4/EYWrYrV1Lt9XUAAAAAAEDdEOzANNsOO5RfVqVgPx8NaBNpdjkAAAAAADQ5rLGD885Z7ZbbY3gfw7ogJUq+PmSMAAAAAADUF8EOzpu5y/fpxW/3qbDcJZvVIrfHkCSN7sJjWAAAAAAAnAmmSeCktmQV6ev0Yw1yrfKqaj3z9R4VlrskyRvqSNKFnVk4GQAAAACAM0GwgxOqqvbosudX6rb5qdpzrOSsr/fV9mMqr3KrTatAffqrC7zHQ/x8FBPqf9bXBwAAAACgJSLYwQmlZhZ4v9522FGvtm6PoT9/lq5/LtkjSdqXW6p/LdsnSZraJ0E9EsLULipIknRFv4QGqhgAAAAAgJaHNXZwQt/szPF+veNIcb3a/mvZPr30XYYkaefREn25/ahcbkPBfj762YBESdKC2wbr3Q2HdMsF7RquaAAAAAAAWhiCHRzHWe3WV+lHva/T6xHsHMwv198X7/a+/nTrEUnS6M7RenRKdyVGBEqS4sMD9OuLOjZQxQAAAAAAtEwEOy2UYRhyVLiUVVChQ4XlOlT44/+nHiiUo8LlPXd7drEMw5DFYjntdV9ZsV/VHkMD20aoym2opNKlWZd01diurevUHgAAAAAA1B3BTguQV+rUx5uzdbCg/CchToVKndUnbWOzWjT3+v668/UNKip36coXVyk+PEB2m1UFZVW65YJ2GtXpx23KM/LK9NRXu/TZ9zN07h3bScM6tCLMAQAAAADgHCLYaQH+8PF2b+Dyv6JD/JQYEaDEiMDv/z9AdqtVHVoHqX+bSA3t0Erf7cnTxoNF2niwyNtu2e5cdY0L1axLumjbYYf+8c0eVVV7JEl9ksIJdQAAAAAAOA8IdlqAjQcKJUnXDEhSz8SwWkGOv912yrav3DhQadkOHXVUKruoQiWV1dp9rERfbD+qHUeKdcOr67znjugYpbtGdVD/NhGEOgAAAAAAnAcEO81cQVmVjjgqJUkPT+6mYL/6Dbmvj1X9kiOOO55X6tSD723V1ztyFBFo1yOTu2lqnwQCHQAAAAAAziOCnWZue7ZDktS2VWC9Q51TiQr20wvX9teKvbnqkxShyCDfBrs2AAAAAACoG4KdZm57ds1W5d3jwxr82r4+Vo3pEtPg1wUAAAAAAHVjNbsAnFs/BDvd4kNNrgQAAAAAADQ0gp1mrNrt0aq9eZJqdqoCAAAAAADNC8FOM7Yuo0D5ZVWKCLRrULtIs8sBAAAAAAANjGCnGft02xFJ0oTusbLbGGoAAAAAAJobfttvpiqq3Pp0S7YkaWLPOJOrAQAAAAAA5wK7YjVRlS63Zi/aqS/Sjmpizzi1aRWogrIqje7SWr0SwvTxlsMqrqxWUmSAhqdEmV0uAAAAAAA4Bwh2mqhXVmRo3qpMSdKrKzO8x//xzR5FBfupqtotSbpucBvZrBYzSgQAAAAAAOcYwU4TVFzp0tzl+487nhgRoKJyl/JKnZKkzjEh+vnA5PNdHgAAAAAAOE8IdpoYwzD0yIdpclS41CE6SJN6xevZb/ZIkv52VW/1bxOh1MwCuQ1DwzpEMVsHAAAAAIBmjGCnifnv+ix9uDlbNqtFf7mil+LC/PXS8v1KjgzU4HaRslotGsaaOgAAAAAAtAgEO03I9myH/vDxdknSA+M7a1C7SEnSN/ePUpCvj6zMzgEAAAAAoEUh2GkiSipdunvBRlVVezSmS2vdObK997348AATKwMAAAAAAGaxml0A6mbO4t3KzC9XQniAnv5Zb2bnAAAAAAAAZuw0VuVV1copdmrn0WLNW5WpNfsLJElPXNFTEUG+JlcHAAAAAAAaA4KdRsQwDK3PLNQ7qVn6fNsRlVW5a73fOzFMIzuyMDIAAAAAAKhBsNNIlFS6dOu8VK3LLPAes1ktcnsMtQryVVSwnx6Z3F0WC49gAQAAAACAGgQ7jYBhGLrrjQ1al1mgALtNk3vH6WcDktQrMUzVbkNBfgwTAAAAAAA4HolBI5B6oFAr9+bL327VO3cNVY+EMO97ZDoAAAAAAOBkiA1M5Kz2aG9esR79eLsk6bLeCbVCHQAAAAAAgFMh2DHR4cIKXfLsSu/r6YOTTawGAAAAAAA0NQQ7JgoLtCsq2FehAXaN7BitXonM1gEAAAAAAHVHsGOiVkG+Sn1onNllAAAAAACAJspqdgEAAAAAAAA4M/UKdtLS0jRw4EBFRERo5syZMgzjtG2WLVumrl27KioqSnPmzKnzewAAAAAAADi1Ogc7TqdTkydPVv/+/ZWamqr09HTNmzfvlG1yc3M1ZcoUTZs2TatXr9aCBQu0dOnS074HAAAAAACA06vzGjuLFi2Sw+HQnDlzFBgYqCeeeEJ33323br755pO2WbBggeLi4vTwww/LYrHokUce0SuvvKLRo0ef8r2TcTqdcjqd3tfFxcWSJJfLJZfLVddbMd0PtTalmpsL+t58jIH5GAPzMQbmov/NRf83DoyD+RgD8zEG5qL/T6+ufWMx6vI8laTHHntMa9eu1eeffy5JMgxDrVq1UkFBwUnb3HzzzQoICNALL7wgSTpy5Iguuugipaenn/K9k3n00Uf12GOPHXf8zTffVGBgYF1uAwAAAAAAoNErLy/X9OnT5XA4FBoaetLz6jxjp7i4WO3atfO+tlgsstlsKiwsVERExEnbdOvWzfs6NDRUhw8fPu17JzNr1izdd999ta6flJSk8ePHn/ImGxuXy6XFixdr3LhxstvtZpfTotD35mMMzMcYmI8xMBf9by76v3FgHMzHGJiPMTDX/7d370FR1u0bwK9nD3IQBEktQtSMAvNAWk5leRzHQ2OJoel0wBnNLDpZZjUdtHLyrUwzsbTQZjKtzMp0lKnME2E5TAeCKEessFQqSGFBCFj2/v3Bj+cNXpWDC/ezu9fnr+BZmu9e1+7e+OXZZ5l/8xrepdScFm/sOBwOBAUFNfpecHAwKisrz7ix0/RnGm7f3LEzCQoK+p81AIDT6fTJB4KvrtsfMHt97EAfO9DHDnQxf13M3xrYgz52oI8d6GL+Z9bSXFp88eSoqCgUFxc3+l55eTk6derU4p/59+3PdoyIiIiIiIiIiJrX4o2doUOH4sCBA+bXhYWFqK6uRlRUVIt/JicnBzExMc0eIyIiIiIiIiKi5rV4Y2fEiBEoKyvD+vXrAQDPP/88xo4dC7vdDpfLddqrNd94443IysrCnj174Ha78dJLL2H8+PHNHiMiIiIiIiIioua16ho7b7zxBm655RYsWLAAdXV12LdvHwBg0KBBWLFiBZKSkhr9TLdu3bBs2TKMHz8eERER6Ny5M9atW9fsMSIiIiIiIiIial6LN3YAICkpCQUFBfj6668xbNgwdO/eHUD927LOJDU1FePGjcNPP/2EkSNHNvr0qrMdIyIiIiIiIiKis2vVxg4AxMTEtPpaOHFxcYiLi2v1MSIiIiIiIiIiOrMWX2OHiIiIiIiIiIishRs7REREREREREQ+qtVvxbISEQEAuFwu5ZW0Tm1tLSorK+FyueB0OrWXE1CYvT52oI8d6GMHupi/LuZvDexBHzvQxw50Mf/mNex1NOx9nIlPb+yUl5cDAGJjY5VXQkRERERERETkfeXl5YiIiDjjcUOa2/qxMI/Hg+PHjyM8PByGYWgvp8VcLhdiY2Px+++/85PAOhiz18cO9LEDfexAF/PXxfytgT3oYwf62IEu5t88EUF5eTkuvPBC2GxnvpKOT5+xY7PZ0LNnT+1ltFmXLl34AFbC7PWxA33sQB870MX8dTF/a2AP+tiBPnagi/mf3dnO1GnAiycTEREREREREfkobuwQEREREREREfkobuwoCAoKwqJFixAUFKS9lIDD7PWxA33sQB870MX8dTF/a2AP+tiBPnagi/l7j09fPJmIiIiIiIiIKJDxjB0iIiIiIiIiIh/FjR0iIiIiIiIiIh/FjR0iIiIiIiIiIh/FjR0iIiIiIiIiIh/FjR0i8rri4mK43W7tZQQsXhOfiLRxDujjLCAiK+A86Bjc2PGy2tpa7SUEJBFBVVUV3nnnHfz888/aywlYRUVFmDx5MqZOnYqysjLt5QSkiooKVFRUaC8j4HEW6OAs0Mc5YA2cBfo4B3RxHujjPOhY3NjxooKCAowZMwYul0t7KQHHMAz88ssvSE1NxRdffMFdYQWPPPIIevXqhdraWuTn5/N5oOC5555DYmIiZs+ejQ0bNpgd8K+2HYuzQA9ngS7OAWvgLNDHOaCP80AX50HH48aOFxUVFWH//v148803tZcScEQEoaGhAIDPPvsMOTk5ugsKILm5uYiIiMCnn36KzMxMZGRkICkpCcePH9deWkA5evQo3nvvPaSlpeHmm2/Gl19+ifvuu097WQGJs0APZ4EOzgHr4CywBs4BfZwHOjgP9HBjxwsa/gKSk5ODsWPH4sknn8SRI0eUVxU4RASGYaCyshJutxtutxtfffUVSktLtZcWMDZt2oTvv/8e11xzDcrKyrB//36Eh4cD4F8IO0pmZiZOnDiBiRMnYurUqUhLS8Pnn3+Obdu2wTAM7eUFBM4CXZwFujgHrIGzQBfngDVwHujiPNDBjZ02KC8vx4svvojt27fjxIkTMAwDHo8HO3fuRHp6Oq699lo8/PDD2sv0S02zB2D+olJaWopp06bhxhtvxIEDB5Cdna25VL/V0MG2bdtQWlqKQYMGYcKECQDq308eERGBa665Bjt37gQA/iLpZSKC6upqbN++HQDg8XgAAPHx8aiursbhw4cBAHa7HUuWLMFTTz3F6yy0E84CPZwFujgH9HEWWAPngD7OA12cB9bBjZ1WKioqwtChQ5GVlYXXX38dDz30ED777DPYbDasXr0avXv3xtq1a/HRRx8hMzNTe7l+5XTZ79692zxeVVWF7Oxs3HbbbejevTvy8vJQUlKC3377TXHV/uXfHaSnp2PevHlmB263G06nE7W1tQgPD0dERASA//6ySd5hGAby8vIwefJk5Ofnw2arfxkPDQ3F8OHDsWnTJvO2M2fORGRkJJYvXw6AXXgTZ4EezgJdnAPWwFmgj3NAH+eBLs4Da+HGTivl5OQgJCQEmzZtwoYNGzBhwgTcc889AICePXvC7XYjNjYWqampmDdvnu5i/UzT7CdOnIi5c+eax10uF/r16wcAuPPOO7F161YMGTIEq1ev5ouIl5ytA4fDAY/HA6fTiS5dumDz5s0AYP6ySd6zb98+iAgWLlxofi8hIQGDBw/GoUOHkJeXZ35/yZIlWLp0KWpqatiFF3EW6OEs0MU5YB2cBbo4B/RxHujiPLAWJttKf//9N44dO4aQkBBERERgxowZ6NOnj3maZcPpZWlpafj555+xdu1azeX6labZT58+Hb1798aDDz4IoP4FJCQkBIcPH8b8+fORl5eHiy66CNOnT+eLiJecroN/P/4bTJ06FZWVlfj111+VVuqfPB4P3G43cnNz8fbbb2P79u3YsmULgPrXnkmTJsHpdOLdd981f2bw4MG49NJL8cknn2gt2y9xFujhLNDFOaCPs8AaOAf0cR7o4jywFj6iW0FEEBcXh/PPP998TzMAvPbaa3j//feRm5sLu92O6upqAMCyZcvw2GOP8UJdXnCm7FevXo0PP/wQ+fn5OHnyJLZs2YKrrroKffv2xSeffILIyEh89913/IhDL2ju8Z+Xl2cOyerqalxwwQX4/ffftZbrlwzDgMPhwLBhw3Drrbfi6aefxoIFC1BTUwMAGDJkCMaPH49vvvkGixcvBlD//vLi4mJcfPHFmkv3K5wFejgLdHEOWANngT7OAX2cB7o4DyxIqFlut1vcbreIiBw7dkzmzJkjDz74oNTU1Ji3uffee2X8+PHm7Rv06tVL3nvvvY5dsB9pSfZ33323TJ8+XY4fPy7Tpk2Tb7/91jy2b98+OXXqVIev25+09vHfIDY2VpYvX96ha/VXbrdbPB7PaY9FR0fLf/7zH/Pr6upq2b17t0RGRsqoUaMkOjpaRo4cKS6Xq6OW67c4C/RwFujiHLAGzgJ9nAP6OA90cR5YlyHCzxw7nYZYPB4P7HY7AODzzz9HQUEBKioqkJubi+TkZCQlJQEA/vrrLyQkJGD//v3o168famtr4XQ6UVlZidDQUK274ZPakn18fDy+/vpr8y9R8v8fc0htc66PfwD44IMPEB8fj4EDB6rcB193ug527dqFnJwczJo1C5GRkTAMAx9++CFmzpyJw4cP44ILLoDH44HNZkN+fj6ysrIQHByMMWPGIDY2VvPu+JR/v257PB7zU044C9rfuWbPWXBuvPnYBzgH2qq5HjgL2l9JSQmioqLMMw5EhHOgg51rB5wH58abzwGA86Aj8K1YAI4cOYKZM2di0aJFyMjIAFD/8WyGYcBut+Po0aOYMmUKbrjhBgQHByMlJQUxMTF4++23cfToUQD1p8UmJCSgsrISAOB0OgGAL+DN8Gb2/z69lS/cLdcej3+g/v20fPFumZZ2MHnyZAQHByMiIsJ8jCcnJyMxMRFPPPFEo/9n//79MXfuXMycOZO/yLfQ1q1bMWLECEyZMgWvvvoqgPpPdeAsaH/ezJ6zoPXa47EPcA60Vkt74CxoX1u3bsWcOXNw8OBBAJwDGrzVAedB23j7OQBwHnQInROFrGPv3r0SFhYmycnJkpSUJGFhYZKdnS0i9aeazZ8/X6KioiQlJUWOHDli/tyPP/4os2fPloEDB0pmZqY89dRTEhYWJoWFhVp3xecwe33sQF9bO2g4LiLy008/iWEY5s9R623ZskWioqJk8eLFkp6eLkFBQWaedXV1fC60I2avi/lbQ1t7EOEs8JaGt7nt2rVLbDabrFq1SioqKszjfC60P3agi/n7toDf2Jk3b57MmzdPRERKS0tl1qxZMmnSJBERmTFjhowYMUIyMzPN2zd9b/OcOXOkf//+ctlll8nGjRs7buF+gNnrYwf6WttBUw2/0K9Zs0ZKSkraf8F+KjU1VVauXGl+feutt8pjjz0mHo+Hz4V2xux1MX9raG0PTXEWeM/69evFMAy58847Zffu3SJSP4+HDx/O50IHYQe6mL9vcmifMdTRDh48iJCQEHTv3h2hoaGoqqpCnz59AABhYWHo168fysrKAADPPfcc+vbt2+jnG07jq6urg91ux5o1a1BWVoauXbua18Sg02P2+tiBvnPtoKmG9z7PnTu3Xdftbxp66NatGzp37ozIyEh4PB7z+MmTJ5GSkgLDMLBy5Up07doVDsd/RyafC23H7HUxf2s41x6a4ixovYYOzj//fAQHB6OmpgadOnVCt27dMHr0aNhsNmRlZeHqq6/G8uXL0aNHD/P6IgCfC97ADnQxfz+jtqXUwVwul0yaNEnCwsLkyiuvlOTkZBER2bNnjxQWFpo7jmlpaTJ48GDNpfodZq+PHehjB9bQtIebbrpJRESKi4vlzz//lLq6Onn99dfFMAwZMmSIzJgxQ6qqqkTkf/8yRa3D7HUxf2tgD/rONI8bPPvsszJ//nzJzc2V5ORk2bFjR6Pj7OHcsQNdzN8/BczFk9966y3U1NTg4MGDePTRR5GVlYVVq1Zh1KhR6N27t7nj+M8//yA+Ph5A/YWi6Nwxe33sQB87sIamPXz55Zd45ZVX0K1bN/To0QM2mw1jx45Fbm4unnnmGRw6dAizZ88GgEZ/TafWY/a6mL81sAd9p+tgxYoV5vGePXvijz/+wMCBA3HFFVcgMzMTCxcuxObNmwHwIrzewA50MX//FDAbO++//z6uu+46xMTEYPLkybj77ruxd+9ec0jW1dUBAIqKisz/Ptspr9RyzF4fO9DHDqyhaQ933XUXvvjiC7MHj8eDvn37YsCAAZg0aRLWr1+PHTt2oLi4uNHpx9R6zF4X87cG9qCvaQdz585FVlaW2UF2djYuu+wyAPWfaJWWloZ33nnHfNs0nTt2oIv5+ye//FdDbm4uMjIyMGrUKCQkJCAyMrLRR6w5nU6Ul5fDbrfDZrOZ7wsEgO+++w4pKSkAgJ07d+Ljjz/GypUrOUxbiNnrYwf62IE1tLYHj8cDm82GsrIyREREAABOnDiByy+/HG63GyLCv1K1ELPXxfytgT3oa20HAJCQkIDMzEyMHDkShYWF5sc6cw63DTvQxfwDh9+dsbN3714MHz4cBQUFePbZZ7FgwQKUlZVh1qxZGD16tHkhp5iYGPz9998AALvdbu5QhoSE4OTJk5g+fTquv/56hIeH80HcQsxeHzvQxw6soS092Gw2/PHHH3jxxReRlJSETz/9FC+88AL69OmD6Oho/oOqhZi9LuZvDexBX1s6AICCggJkZGTgqquuwo8//og333yT/6htI3agi/kHGIXr+rSrRYsWyZQpU0REpKSkRB544AHzaxGRuro6ERFJSUmR1NTURt87deqUGIYhhmHIzTffLGVlZR28et/G7PWxA33swBra0kODgoICSU5OlpEjR8ott9wiFRUVHbdwP8DsdTF/a2AP+traQUlJiRw8eLDR/6vh4+SpddiBLuYfWHz+jJ1t27Zh2rRpWLVqFf7880+Ul5fj1KlTAIDzzjsPL7/8MrKzs7F161YAaPTRaw3vE7TZbDh8+DDq6uqwZMkS5OTkYNOmTejSpUuH3x9fwuz1sQN97MAavNEDABw6dAhxcXH44IMPsGPHDmzcuBGdO3fu0Pvia5i9LuZvDexBn7c6KC0tRXx8fKPjPFOhZdiBLuYf4DR2k7xl4cKF0qVLF7njjjtk6NChEh8fLxs2bJChQ4fKL7/8Yt5u3bp1MnjwYPnnn3/M711xxRWya9cuOXTokMTFxUliYqJUVlZq3A2fxOz1sQN97MAavNXDJZdcIgMHDjQ/Wpiax+x1MX9rYA/6vNnBoEGD2EEbsANdzJ98dmPn5MmTMmzYMNmzZ4+I1J+2mpiYKCkpKTJ79mxZuXJlo9snJibKCy+8ICIiv/76q0RHR0u/fv3EZrPJww8/3NHL92nMXh870McOrIE96GH2upi/NbAHfexAHzvQxfxJxIffihUcHAyHw4HQ0FAA9aeXxcfHY9CgQYiJicG3336L3Nxc8/aPP/440tPTISKIjIyEw+FA//79UVRUhKVLl2rdDZ/E7PWxA33swBrYgx5mr4v5WwN70McO9LEDXcyfAB/+VCy73Y4nnngCAwYMgMfjQdeuXXHs2DF06tQJd9xxBxwOB9LS0szbR0ZGolevXnC5XLDb7Thw4AA2b96MHj16KN4L38Ts9bEDfezAGtiDHmavi/lbA3vQxw70sQNdzJ8AH97YcTqdGDduHEJDQ2EYBtxuN8LCwhAVFYXY2FjcfvvtyM/Px4wZM/DVV18hLS0N5eXlCA0NRXh4OC688ELtu+CzmL0+dqCPHVgDe9DD7HUxf2tgD/rYgT52oIv5E+DDGzv/ZhgGHA4HCgsL4XA4AAAjRozAxo0bYRgGkpKSUFlZifT0dDidTuXV+hdmr48d6GMH1sAe9DB7XczfGtiDPnagjx3oYv6By6G9AG/57bffUFFRgQkTJgAAFi9ejD59+uDdd9/FiRMn0LVrVxiGobxK/8Ts9bEDfezAGtiDHmavi/lbA3vQxw70sQNdzD8w+cUZOwBQVVWFiy++GJs3b8aAAQOwfPlyREdHAwCioqL44G1HzF4fO9DHDqyBPehh9rqYvzWwB33sQB870MX8A5TSp3F53UcffSSGYUh4eLgsWbJEezkBhdnrYwf62IE1sAc9zF4X87cG9qCPHehjB7qYf2AyRES0N5e84YcffkBGRgbuv/9+BAcHay8noDB7fexAHzuwBvagh9nrYv7WwB70sQN97EAX8w9MfrOxQ0REREREREQUaPzmGjtERERERERERIGGGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD6KGztERERERERERD7q/wBQcN5c9sFYMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "the_date = '2022-01-01'\n",
    "\n",
    "df = pd.read_csv('dddd.csv',index_col=0,parse_dates=True)\n",
    "# df = df.drop(['展期','动量','反转','反套','正套'],axis=1)\n",
    "# df = df[['展期','动量','反转','反套','正套']]\n",
    "df = df[the_date:]\n",
    "w = (1/df[the_date:].std())/(1/df[the_date:].std()).sum()\n",
    "rrr = (w*df).sum(1)\n",
    "rrr.cumsum().plot(figsize=(14,6),grid=True)\n",
    "df['组合'] = rrr\n",
    "cols = df.columns\n",
    "df.cumsum().plot(figsize=(14,6),grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a41e956b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.094145</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1\n",
       "0  1.000000  0.094145\n",
       "1  0.094145  1.000000"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pp = pd.concat([df[['展期','动量','反转','反套','正套']].mean(1),df.drop(['展期','动量','反转','反套','正套','组合'],axis=1).mean(1)],axis=1)\n",
    "pp.resample('W').sum().corr('spearman')\n",
    "# pp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "190a576e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>展期</th>\n",
       "      <th>动量</th>\n",
       "      <th>反转</th>\n",
       "      <th>反套</th>\n",
       "      <th>正套</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>0.002350</td>\n",
       "      <td>0.012269</td>\n",
       "      <td>0.010163</td>\n",
       "      <td>0.000894</td>\n",
       "      <td>-0.001315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>-0.000575</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.000182</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>0.000193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>-0.004383</td>\n",
       "      <td>0.005213</td>\n",
       "      <td>0.004223</td>\n",
       "      <td>-0.000932</td>\n",
       "      <td>0.003273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.006896</td>\n",
       "      <td>0.006550</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>0.000685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.001898</td>\n",
       "      <td>-0.004110</td>\n",
       "      <td>-0.002855</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.001506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-17</th>\n",
       "      <td>0.003319</td>\n",
       "      <td>-0.000688</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.000534</td>\n",
       "      <td>0.001755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-18</th>\n",
       "      <td>0.000896</td>\n",
       "      <td>-0.003272</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>0.000095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-19</th>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.004630</td>\n",
       "      <td>-0.000326</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>0.000121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>618 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  展期        动量        反转        反套        正套\n",
       "2022-01-04  0.002350  0.012269  0.010163  0.000894 -0.001315\n",
       "2022-01-05 -0.000575 -0.001892 -0.000182  0.002264  0.000193\n",
       "2022-01-06 -0.004383  0.005213  0.004223 -0.000932  0.003273\n",
       "2022-01-07  0.006896  0.006550  0.000121 -0.001430  0.000685\n",
       "2022-01-10  0.001898 -0.004110 -0.002855  0.000379  0.001506\n",
       "...              ...       ...       ...       ...       ...\n",
       "2024-07-17  0.003319 -0.000688 -0.000396  0.000534  0.001755\n",
       "2024-07-18  0.000896 -0.003272  0.001935  0.000530  0.000095\n",
       "2024-07-19 -0.002407 -0.004630 -0.000326 -0.000175  0.000121\n",
       "2024-07-22       NaN       NaN       NaN       NaN       NaN\n",
       "2024-07-23       NaN       NaN       NaN       NaN       NaN\n",
       "\n",
       "[618 rows x 5 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['展期','动量','反转','反套','正套']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a516276f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>国债</th>\n",
       "      <th>股指日度</th>\n",
       "      <th>股指月度</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.010095</td>\n",
       "      <td>0.001409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>-0.000907</td>\n",
       "      <td>0.010248</td>\n",
       "      <td>-0.009234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>-0.001353</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>0.008079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>-0.004476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.001007</td>\n",
       "      <td>0.008952</td>\n",
       "      <td>-0.001867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-17</th>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>0.004134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-18</th>\n",
       "      <td>-0.000662</td>\n",
       "      <td>-0.005736</td>\n",
       "      <td>0.000263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-19</th>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.006807</td>\n",
       "      <td>0.002961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>618 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  国债      股指日度      股指月度\n",
       "2022-01-04  0.000083  0.010095  0.001409\n",
       "2022-01-05 -0.000907  0.010248 -0.009234\n",
       "2022-01-06 -0.001353 -0.000859  0.008079\n",
       "2022-01-07  0.000083  0.003895 -0.004476\n",
       "2022-01-10  0.001007  0.008952 -0.001867\n",
       "...              ...       ...       ...\n",
       "2024-07-17  0.000316  0.004925  0.004134\n",
       "2024-07-18 -0.000662 -0.005736  0.000263\n",
       "2024-07-19  0.000929  0.006807  0.002961\n",
       "2024-07-22       NaN  0.021351       NaN\n",
       "2024-07-23       NaN       NaN       NaN\n",
       "\n",
       "[618 rows x 3 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(['展期','动量','反转','反套','正套','组合'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "6df599f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2022-01-04</th>\n",
       "      <td>0.002350</td>\n",
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       "      <td>0.010163</td>\n",
       "      <td>0.000083</td>\n",
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       "      <td>0.000894</td>\n",
       "      <td>0.002040</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>-0.000575</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.000182</td>\n",
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       "      <td>-0.009234</td>\n",
       "      <td>0.000193</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>0.000022</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>-0.004383</td>\n",
       "      <td>0.005213</td>\n",
       "      <td>0.004223</td>\n",
       "      <td>-0.001353</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>0.008079</td>\n",
       "      <td>0.003273</td>\n",
       "      <td>-0.000932</td>\n",
       "      <td>0.000825</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.006896</td>\n",
       "      <td>0.006550</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>-0.004476</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>0.000351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.001898</td>\n",
       "      <td>-0.004110</td>\n",
       "      <td>-0.002855</td>\n",
       "      <td>0.001007</td>\n",
       "      <td>0.008952</td>\n",
       "      <td>-0.001867</td>\n",
       "      <td>0.001506</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.000378</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2024-07-17</th>\n",
       "      <td>0.003319</td>\n",
       "      <td>-0.000688</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>0.004134</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.000534</td>\n",
       "      <td>0.001055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-18</th>\n",
       "      <td>0.000896</td>\n",
       "      <td>-0.003272</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>-0.000662</td>\n",
       "      <td>-0.005736</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>-0.000056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-19</th>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.004630</td>\n",
       "      <td>-0.000326</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.006807</td>\n",
       "      <td>0.002961</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>0.000093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
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       "<p>618 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  展期        动量        反转        国债      股指日度      股指月度  \\\n",
       "2022-01-04  0.002350  0.012269  0.010163  0.000083  0.010095  0.001409   \n",
       "2022-01-05 -0.000575 -0.001892 -0.000182 -0.000907  0.010248 -0.009234   \n",
       "2022-01-06 -0.004383  0.005213  0.004223 -0.001353 -0.000859  0.008079   \n",
       "2022-01-07  0.006896  0.006550  0.000121  0.000083  0.003895 -0.004476   \n",
       "2022-01-10  0.001898 -0.004110 -0.002855  0.001007  0.008952 -0.001867   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2024-07-17  0.003319 -0.000688 -0.000396  0.000316  0.004925  0.004134   \n",
       "2024-07-18  0.000896 -0.003272  0.001935 -0.000662 -0.005736  0.000263   \n",
       "2024-07-19 -0.002407 -0.004630 -0.000326  0.000929  0.006807  0.002961   \n",
       "2024-07-22       NaN       NaN       NaN       NaN  0.021351       NaN   \n",
       "2024-07-23       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "                  正套        反套        组合  \n",
       "2022-01-04 -0.001315  0.000894  0.002040  \n",
       "2022-01-05  0.000193  0.002264  0.000022  \n",
       "2022-01-06  0.003273 -0.000932  0.000825  \n",
       "2022-01-07  0.000685 -0.001430  0.000351  \n",
       "2022-01-10  0.001506  0.000379  0.000378  \n",
       "...              ...       ...       ...  \n",
       "2024-07-17  0.001755  0.000534  0.001055  \n",
       "2024-07-18  0.000095  0.000530 -0.000056  \n",
       "2024-07-19  0.000121 -0.000175  0.000093  \n",
       "2024-07-22       NaN       NaN  0.000496  \n",
       "2024-07-23       NaN       NaN  0.000000  \n",
       "\n",
       "[618 rows x 9 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "151fa18c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>展期</th>\n",
       "      <th>动量</th>\n",
       "      <th>反转</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>展期</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.118695</td>\n",
       "      <td>0.036522</td>\n",
       "      <td>0.146598</td>\n",
       "      <td>0.413752</td>\n",
       "      <td>0.572750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>动量</th>\n",
       "      <td>0.118695</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.103342</td>\n",
       "      <td>0.051506</td>\n",
       "      <td>0.242957</td>\n",
       "      <td>0.452983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反转</th>\n",
       "      <td>0.036522</td>\n",
       "      <td>-0.103342</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.352993</td>\n",
       "      <td>-0.150479</td>\n",
       "      <td>0.383260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反套</th>\n",
       "      <td>0.146598</td>\n",
       "      <td>0.051506</td>\n",
       "      <td>0.352993</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.288039</td>\n",
       "      <td>0.647097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>正套</th>\n",
       "      <td>0.413752</td>\n",
       "      <td>0.242957</td>\n",
       "      <td>-0.150479</td>\n",
       "      <td>0.288039</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.593685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>组合</th>\n",
       "      <td>0.572750</td>\n",
       "      <td>0.452983</td>\n",
       "      <td>0.383260</td>\n",
       "      <td>0.647097</td>\n",
       "      <td>0.593685</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          展期        动量        反转        反套        正套        组合\n",
       "展期  1.000000  0.118695  0.036522  0.146598  0.413752  0.572750\n",
       "动量  0.118695  1.000000 -0.103342  0.051506  0.242957  0.452983\n",
       "反转  0.036522 -0.103342  1.000000  0.352993 -0.150479  0.383260\n",
       "反套  0.146598  0.051506  0.352993  1.000000  0.288039  0.647097\n",
       "正套  0.413752  0.242957 -0.150479  0.288039  1.000000  0.593685\n",
       "组合  0.572750  0.452983  0.383260  0.647097  0.593685  1.000000"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('W').sum().corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e14f9abb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a32e4a01",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "979cc3df",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "948135db",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddd = pd.concat([\n",
    "    cal年化收益率(df[cols]),\n",
    "    cal夏普比率(df[cols]),\n",
    "    cal收益平均回撤(df[cols]),\n",
    "    cal收益最大回撤(df[cols]),\n",
    "    cal最大回撤(df[cols]),\n",
    "    pd.Series([get_回撤s(df[col])[1] for col in cols],index=cols),\n",
    "    pd.Series([get_回撤s(df[col])[2] for col in cols],index=cols),\n",
    "    cal周度胜率(df[cols]),\n",
    "    cal周度盈亏比(df[cols]),\n",
    "    pd.Series([cal最大下潜期(df[col]) for col in cols],index=cols),\n",
    "    pd.Series([get_下潜期s(df[col])[1] for col in cols],index=cols),\n",
    "    pd.Series([get_下潜期s(df[col])[2] for col in cols],index=cols),\n",
    "    pd.Series([cal最大下潜期结束时间(df[col]) for col in cols],index=cols),\n",
    "    pd.Series([cal当前回撤(df[col]) for col in cols],index=cols),\n",
    "    pd.Series([cal当前下潜期(df[col]) for col in cols],index=cols),\n",
    "],axis=1)\n",
    "ddd.columns = ['年化收益率','夏普','收益/平均回撤','收益/最大回撤','最大回撤','第2大回撤','第3大回撤',\n",
    "               '周度胜率','周度盈亏比','最大下潜期','第2大下潜期','第3大下潜期','最大下潜期结束时间','当前回撤','当前下潜期']\n",
    "ddd['当前回撤/最大回撤'] = ddd['当前回撤']/ddd['最大回撤']\n",
    "ddd['当前回撤/第2大回撤'] = ddd['当前回撤']/ddd['第2大回撤']\n",
    "ddd['当前回撤/第3大回撤'] = ddd['当前回撤']/ddd['第3大回撤']\n",
    "ddd['当前下潜期/最大下潜期'] = ddd['当前下潜期']/ddd['最大下潜期']\n",
    "ddd['当前下潜期/第2大下潜期'] = ddd['当前下潜期']/ddd['第2大下潜期']\n",
    "ddd['当前下潜期/第3大下潜期'] = ddd['当前下潜期']/ddd['第3大下潜期']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d80bc8c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年化收益率</th>\n",
       "      <th>夏普</th>\n",
       "      <th>收益/平均回撤</th>\n",
       "      <th>收益/最大回撤</th>\n",
       "      <th>最大回撤</th>\n",
       "      <th>第2大回撤</th>\n",
       "      <th>第3大回撤</th>\n",
       "      <th>周度胜率</th>\n",
       "      <th>周度盈亏比</th>\n",
       "      <th>最大下潜期</th>\n",
       "      <th>...</th>\n",
       "      <th>第3大下潜期</th>\n",
       "      <th>最大下潜期结束时间</th>\n",
       "      <th>当前回撤</th>\n",
       "      <th>当前下潜期</th>\n",
       "      <th>当前回撤/最大回撤</th>\n",
       "      <th>当前回撤/第2大回撤</th>\n",
       "      <th>当前回撤/第3大回撤</th>\n",
       "      <th>当前下潜期/最大下潜期</th>\n",
       "      <th>当前下潜期/第2大下潜期</th>\n",
       "      <th>当前下潜期/第3大下潜期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>展期</th>\n",
       "      <td>0.078994</td>\n",
       "      <td>1.321418</td>\n",
       "      <td>4.575258</td>\n",
       "      <td>1.466203</td>\n",
       "      <td>0.053877</td>\n",
       "      <td>0.053866</td>\n",
       "      <td>0.034853</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>1.025448</td>\n",
       "      <td>179</td>\n",
       "      <td>...</td>\n",
       "      <td>76</td>\n",
       "      <td>2023-02-17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.067039</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.157895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>动量</th>\n",
       "      <td>0.100761</td>\n",
       "      <td>1.426466</td>\n",
       "      <td>6.506728</td>\n",
       "      <td>1.628075</td>\n",
       "      <td>0.061889</td>\n",
       "      <td>0.050676</td>\n",
       "      <td>0.050099</td>\n",
       "      <td>0.593750</td>\n",
       "      <td>1.114540</td>\n",
       "      <td>130</td>\n",
       "      <td>...</td>\n",
       "      <td>72</td>\n",
       "      <td>2022-11-24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.038462</td>\n",
       "      <td>0.044248</td>\n",
       "      <td>0.069444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反转</th>\n",
       "      <td>0.081957</td>\n",
       "      <td>1.827233</td>\n",
       "      <td>6.075093</td>\n",
       "      <td>1.500970</td>\n",
       "      <td>0.054603</td>\n",
       "      <td>0.016329</td>\n",
       "      <td>0.014221</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>1.127374</td>\n",
       "      <td>238</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>2023-02-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.012605</td>\n",
       "      <td>0.050847</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>反套</th>\n",
       "      <td>0.032250</td>\n",
       "      <td>2.492874</td>\n",
       "      <td>23.020229</td>\n",
       "      <td>4.653251</td>\n",
       "      <td>0.006931</td>\n",
       "      <td>0.005984</td>\n",
       "      <td>0.005661</td>\n",
       "      <td>0.648438</td>\n",
       "      <td>1.277632</td>\n",
       "      <td>55</td>\n",
       "      <td>...</td>\n",
       "      <td>46</td>\n",
       "      <td>2022-05-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.727273</td>\n",
       "      <td>0.816327</td>\n",
       "      <td>0.869565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>正套</th>\n",
       "      <td>0.032897</td>\n",
       "      <td>1.572569</td>\n",
       "      <td>7.470559</td>\n",
       "      <td>2.128163</td>\n",
       "      <td>0.015458</td>\n",
       "      <td>0.011697</td>\n",
       "      <td>0.008462</td>\n",
       "      <td>0.546875</td>\n",
       "      <td>1.431688</td>\n",
       "      <td>194</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>2023-01-11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.273196</td>\n",
       "      <td>0.757143</td>\n",
       "      <td>0.841270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>组合</th>\n",
       "      <td>0.048309</td>\n",
       "      <td>3.315290</td>\n",
       "      <td>24.128303</td>\n",
       "      <td>4.023108</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>0.006532</td>\n",
       "      <td>0.005163</td>\n",
       "      <td>0.671875</td>\n",
       "      <td>1.518736</td>\n",
       "      <td>114</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>2022-11-10</td>\n",
       "      <td>0.000678</td>\n",
       "      <td>3</td>\n",
       "      <td>0.056437</td>\n",
       "      <td>0.103741</td>\n",
       "      <td>0.131255</td>\n",
       "      <td>0.026316</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.125000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       年化收益率        夏普    收益/平均回撤   收益/最大回撤      最大回撤     第2大回撤     第3大回撤  \\\n",
       "展期  0.078994  1.321418   4.575258  1.466203  0.053877  0.053866  0.034853   \n",
       "动量  0.100761  1.426466   6.506728  1.628075  0.061889  0.050676  0.050099   \n",
       "反转  0.081957  1.827233   6.075093  1.500970  0.054603  0.016329  0.014221   \n",
       "反套  0.032250  2.492874  23.020229  4.653251  0.006931  0.005984  0.005661   \n",
       "正套  0.032897  1.572569   7.470559  2.128163  0.015458  0.011697  0.008462   \n",
       "组合  0.048309  3.315290  24.128303  4.023108  0.012008  0.006532  0.005163   \n",
       "\n",
       "        周度胜率     周度盈亏比  最大下潜期  ...  第3大下潜期   最大下潜期结束时间      当前回撤  当前下潜期  \\\n",
       "展期  0.625000  1.025448    179  ...      76  2023-02-17       NaN     12   \n",
       "动量  0.593750  1.114540    130  ...      72  2022-11-24       NaN      5   \n",
       "反转  0.625000  1.127374    238  ...      27  2023-02-01       NaN      3   \n",
       "反套  0.648438  1.277632     55  ...      46  2022-05-05       NaN     40   \n",
       "正套  0.546875  1.431688    194  ...      63  2023-01-11       NaN     53   \n",
       "组合  0.671875  1.518736    114  ...      24  2022-11-10  0.000678      3   \n",
       "\n",
       "    当前回撤/最大回撤  当前回撤/第2大回撤  当前回撤/第3大回撤  当前下潜期/最大下潜期  当前下潜期/第2大下潜期  当前下潜期/第3大下潜期  \n",
       "展期        NaN         NaN         NaN     0.067039      0.133333      0.157895  \n",
       "动量        NaN         NaN         NaN     0.038462      0.044248      0.069444  \n",
       "反转        NaN         NaN         NaN     0.012605      0.050847      0.111111  \n",
       "反套        NaN         NaN         NaN     0.727273      0.816327      0.869565  \n",
       "正套        NaN         NaN         NaN     0.273196      0.757143      0.841270  \n",
       "组合   0.056437    0.103741    0.131255     0.026316      0.044776      0.125000  \n",
       "\n",
       "[6 rows x 21 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2e279ce0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>展期</th>\n",
       "      <th>动量</th>\n",
       "      <th>反转</th>\n",
       "      <th>国债</th>\n",
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       "      <th>组合</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>0.002350</td>\n",
       "      <td>0.012269</td>\n",
       "      <td>0.010163</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.010095</td>\n",
       "      <td>0.001409</td>\n",
       "      <td>-0.001315</td>\n",
       "      <td>0.000894</td>\n",
       "      <td>0.002040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>-0.000575</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.000182</td>\n",
       "      <td>-0.000907</td>\n",
       "      <td>0.010248</td>\n",
       "      <td>-0.009234</td>\n",
       "      <td>0.000193</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>0.000022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>-0.004383</td>\n",
       "      <td>0.005213</td>\n",
       "      <td>0.004223</td>\n",
       "      <td>-0.001353</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>0.008079</td>\n",
       "      <td>0.003273</td>\n",
       "      <td>-0.000932</td>\n",
       "      <td>0.000825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.006896</td>\n",
       "      <td>0.006550</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>-0.004476</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>0.000351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.001898</td>\n",
       "      <td>-0.004110</td>\n",
       "      <td>-0.002855</td>\n",
       "      <td>0.001007</td>\n",
       "      <td>0.008952</td>\n",
       "      <td>-0.001867</td>\n",
       "      <td>0.001506</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.000378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-17</th>\n",
       "      <td>0.003319</td>\n",
       "      <td>-0.000688</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>0.004134</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.000534</td>\n",
       "      <td>0.001055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-18</th>\n",
       "      <td>0.000896</td>\n",
       "      <td>-0.003272</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>-0.000662</td>\n",
       "      <td>-0.005736</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>-0.000056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-19</th>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.004630</td>\n",
       "      <td>-0.000326</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.006807</td>\n",
       "      <td>0.002961</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>0.000093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>618 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  展期        动量        反转        国债      股指日度      股指月度  \\\n",
       "2022-01-04  0.002350  0.012269  0.010163  0.000083  0.010095  0.001409   \n",
       "2022-01-05 -0.000575 -0.001892 -0.000182 -0.000907  0.010248 -0.009234   \n",
       "2022-01-06 -0.004383  0.005213  0.004223 -0.001353 -0.000859  0.008079   \n",
       "2022-01-07  0.006896  0.006550  0.000121  0.000083  0.003895 -0.004476   \n",
       "2022-01-10  0.001898 -0.004110 -0.002855  0.001007  0.008952 -0.001867   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2024-07-17  0.003319 -0.000688 -0.000396  0.000316  0.004925  0.004134   \n",
       "2024-07-18  0.000896 -0.003272  0.001935 -0.000662 -0.005736  0.000263   \n",
       "2024-07-19 -0.002407 -0.004630 -0.000326  0.000929  0.006807  0.002961   \n",
       "2024-07-22       NaN       NaN       NaN       NaN  0.021351       NaN   \n",
       "2024-07-23       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "                  正套        反套        组合  \n",
       "2022-01-04 -0.001315  0.000894  0.002040  \n",
       "2022-01-05  0.000193  0.002264  0.000022  \n",
       "2022-01-06  0.003273 -0.000932  0.000825  \n",
       "2022-01-07  0.000685 -0.001430  0.000351  \n",
       "2022-01-10  0.001506  0.000379  0.000378  \n",
       "...              ...       ...       ...  \n",
       "2024-07-17  0.001755  0.000534  0.001055  \n",
       "2024-07-18  0.000095  0.000530 -0.000056  \n",
       "2024-07-19  0.000121 -0.000175  0.000093  \n",
       "2024-07-22       NaN       NaN  0.000496  \n",
       "2024-07-23       NaN       NaN  0.000000  \n",
       "\n",
       "[618 rows x 9 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
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